In the present work, a numerical framework for the design of new multiscale fibre-reinforced cementitious composites is presented. This is accomplished by covering three different length scales, namely the micro-, meso- and macroscale. At the microscale (here defined as ~1 mm), an enhanced fibre-reinforced lattice model is presented for the simulation of strain hardening cementitious composites. On the other hand, the analysis of fibre-reinforced concrete is performed at the mesoscale (~10 mm) by means of a novel lattice-particle model. The main variables in both models are the fibre dimensions (i.e. length and diameter), the fibre volume content and the fibre-matrix bond behaviour. Their contribution to the global mechanical properties is discussed in details. Finally, the structural characterisation of the fibre-reinforced cementitious composites (FRCC) is carried out by means of a hierarchical numerical homogenisation of the material behaviour, integrating the information obtained from lower scales into the macroscale problem (~1 m). The macroscopic response of the resulting material is characterised via three-point bending tests using a continuum damage plastic model. Although the described lattice models can be used independently as design tools in fibre cement-based composites at the micro- or mesoscale, the multiscale procedure described in this paper allows for the development of new types of FRCC by considering the effect of the multiple-scale fibre-reinforcement.

Unlike conventional hydrothennal geothermal technology that utilizes hot water as the energy conversion resources tapped from natural hydrothermal reservoir located at {approx}10 km below the ground surface, Enhanced Geothermal System (EGS) must create a hydrothermal reservoir in a hot rock stratum at temperatures {ge}200 C, present in {approx}5 km deep underground by employing hydraulic fracturing. This is the process of initiating and propagating a fracture as well as opening pre-existing fractures in a rock layer. In this operation, a considerable attention is paid to the pre-existing fractures and pressure-generated ones made in the underground foundation during drilling and logging. These fractures in terms of lost circulation zones often cause the wastage of a substantial amount of the circulated water-based drilling fluid or mud. Thus, such lost circulation zones must be plugged by sealing materials, so that the drilling operation can resume and continue. Next, one important consideration is the fact that the sealers must be disintegrated by highly pressured water to reopen the plugged fractures and to promote the propagation of reopened fractures. In response to this need, the objective of this phase I project in FYs 2009-2011 was to develop temporary cementitious fracture sealing materials possessing self-degradable properties generating when {ge} 200 C-heated scalers came in contact with water. At BNL, we formulated two types of non-Portland cementitioussystems using inexpensive industrial by-products with pozzolanic properties, such as granulated blast-furnace slag from the steel industries, and fly ashes from coal-combustion power plants. These byproducts were activated by sodium silicate to initiate their pozzolanic reactions, and to create a cemetitious structure. One developed system was sodium silicate alkali-activated slag/Class C fly ash (AASC); the other was sodium silicate alkali-activated slag/Class F fly ash (AASF) as the binder of temper

A multi-scale periodic homogenization procedure of the ionic transfers in saturated porous media is proposed. An application on a multi-scale porous material was achieved for establishing models describing a ionic transfer from Nernst-Planck-Poisson-Boltzmann system. The first one is obtained by homogenization from the scale of Debye length to the capillary porosity scale, by taking into account the electrical double layer phenomenon. The second one results from another homogenization procedure from the capillary porosity scale to the scale of the material, where the electrical double layer effects are naturally negligible. A numerical parametric study is conducted on three dimensional elementary cells in order to highlight the effects of the electrical double layer on the ionic transfer parameters. Comparisons with existing experimental data are also presented and discussed. The double homogenization procedure gives homogenized diffusion coefficients very close to those obtained experimentally for chlorides ions from electrodiffusion tests carried out in laboratory.

In the development of new eco-cements for ecologically friendly construction, the porosity, surface structure and chemical nature of the material can influence the bioreceptivity of the surface and the aptitude or not of environmental micro-organisms to form biofilms. Such films are the source of biocontamination that can lead to a degradation in the structural properties over time. Accurate measurement of surface roughness and topography are important to help in the understanding of this interaction. Optical profilers are well adapted to the quantifying of large surface roughness typical of cementitious materials, being more rapid and better able to cope with high roughness compared with stylus and near field probe techniques. But any given surface profiler typically has specific range limits in terms of axial and lateral resolution and field of view, resulting in different roughness values according to the type of optical profiler used. In the present work, unpolished and polished cement paste samples have been measured with two different systems, one using interference microscopy and the other, chromatic confocal sensing. Comparison of the results from both techniques using the method of window re-sizing, more commonly used in tribology, has been used for calculating the average roughness parameters at different scales. The initial results obtained show a successful overlap of the results for the unpolished samples and a slight separation for the polished samples. The validation of the measurements is demonstrated together with a revealing of differences in the measurements on different types of surfaces due to variations in instrument performance.

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

Together with a series of mechanical tests, the interactions and potential bonding between polymeric fibers and cementitious materials were studied using scanning transmission X-ray microscopy (STXM) and microtomography (lCT). Experimental results showed that these techniques have great potential to characterize the polymer fiber-hydrated cement-paste matrix interface, as well as differentiating the chemistry of the two components of a bi-polymer (hybrid) fiber the polypropylene core and the ethylene acrylic acid copolymer sheath. Similarly, chemical interactions between the hybrid fiber and the cement hydration products were observed, indicating the chemical bonding between the sheath and the hardened cement paste matrix. Microtomography allowed visualization of the performance of the samples, and the distribution and orientation of the two types of fiber in mortar. Beam flexure tests confirmed improved tensile strength of mixes containing hybrid fibers, and expansion bar tests showed similar reductions in expansion for the polypropylene and hybrid fiber mortar bars.

The interfacial bond characteristics between carbon fiber and a cement matrix, in high temperature fiber-reinforced cementitious composite systems, can be improved by the oxidative treatment of the fiber surfaces. Compositions and the process for producing the compositions are disclosed. 2 figs.

The interfacial bond characteristics between carbon fiber and a cement matrix, in high temperature fiber-reinforced cementitious composite systems, can be improved by the oxidative treatment of the fiber surfaces. Compositions and the process for producing the compositions are disclosed.

This paper presents details of an original crack-closure system for cementitious materials using shrinkable polymer tendons. The system involves the incorporation of unbonded pre-oriented polymer tendons in cementitious beams. Crack closure is achieved by thermally activating the shrinkage mechanism of the restrained polymer tendons after the cement-based material has undergone initial curing. The feasibility of the system is demonstrated in a series of small scale experiments on pre-cracked prismatic mortar specimens. The results from these tests show that, upon activation, the polymer tendon completely closes the preformed macro-cracks and imparts a significant stress across the crack faces. The potential of the system to enhance the natural autogenous crack healing process and generally improve the durability of concrete structures is addressed.

Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental platforms, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems while using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to best leverage these multiscale models to gain insight into biological systems using quantitative, biomedical engineering methods to analyze data in non-intuitive ways. These topics are discussed with a focus on the future of the field, the current challenges encountered, and opportunities yet to be realized. PMID:23642247

A thermally conductive cement-sand grout for use with a geothermal heat pump system. The cement sand grout contains cement, silica sand, a superplasticizer, water and optionally bentonite. The present invention also includes a method of filling boreholes used for geothermal heat pump systems with the thermally conductive cement-sand grout. The cement-sand grout has improved thermal conductivity over neat cement and bentonite grouts, which allows shallower bore holes to be used to provide an equivalent heat transfer capacity. In addition, the cement-sand grouts of the present invention also provide improved bond strengths and decreased permeabilities. The cement-sand grouts can also contain blast furnace slag, fly ash, a thermoplastic air entraining agent, latex, a shrinkage reducing admixture, calcium oxide and combinations thereof.

In former publications we presented an automated multiscale measurement system (AMMS) based on an adaptable active exploration strategy. The system is armed with several sensors linked by indicator algorithms to identify unresolved defects and to trigger finer resolved measurements. The advantage of this strategy in comparison to single sensor approaches is its high flexibility which is used to balance the conflict between measurement range, resolution and duration. For an initial proof of principle we used the system for inspection of microlens arrays. An even higher challenge for inspection systems are modern micro electro-mechanical systems (MEMS). MEMS consist of critical functional components which range from several millimeters down to micrometers and typically have tolerances in sub-micron scale. This contribution is focused on the inspection of MEMS using the example of micro calibration devices. This new class of objects has completely different surface characteristics and features hence it is necessary to adapted the components of the AMMS. Typical defects found on calibration devices are for example broken actuator combs and springs, surface cracks or missing features. These defects have less influence on the optical properties of the surface and the MEMS surface generates more complex intensity distributions in comparison microlense arrays. At the same time, the surface features of the MEMS have a higher variety and less periodicity which reduce the performance of currently used algorithms. To meet these requirements, we present new indicator algorithms for the automated analysis of confocal as well as conventional imaging data and show initial multiscale inspection results.

We first argue the need for well defined resilience metrics to better evaluate the resilience of complex systems such as (peri-)urban flood management systems. We review both the successes and limitations of resilience metrics in the framework of dynamical systems and their generalization in the framework of the viability theory. We then point out that the most important step to achieve is to define resilience across scales instead of doing it at a given scale. Our preliminary, critical analysis of the series of attempts to define an operational resilience metrics led us to consider a scale invariant metrics based on the scale independent codimension of extreme singularities. Multifractal downscaling of climate scenarios can be considered as a first illustration. We focussed on a flood scenario evaluation method with the help of two singularities γ_s and γ_Max, corresponding respectively to an effective and a probable maximum singularity, that yield an innovative framework to address the issues of flood resilience systems in a scale independent manner. Indeed, the stationarity of the universal multifractal parameters would result into a rather stable value of probable maximum singularity γ_s. By fixing the limit of acceptability for a maximum flood water depth at a given scale, with a corresponding singularity, we effectively fix the threshold of the probable maximum singularity γ_s as a criterion of the flood resilience we accept. Then various scenarios of flood resilient measures could be simulated with the help of Multi-Hydro under upcoming climat scenarios. The scenarios that result in estimates of either γ_Max or γ_s below the pre-selected γ_s value will assure the effective flood resilience of the whole modeled system across scales. The research for this work was supported, in part, by the EU FP7 SMARTesT and INTERREG IVB RainGain projects.

Addition of lithium nitrate admixture to the fresh concrete mixture helps to minimize potential problems related to alkali-silica reaction. For this admixture to function as an effective ASR control measure, it is imperative that the lithium ions remain in the pore solution. However, it was found that about 50% of the originally added lithium ions are removed from the pore solution during early stages of hydration. This paper revealed that the magnitude of the Li{sup +} ion loss is highly dependent on the concentration of Li{sup +} ions in the pore solution and the hydration rate of the cementitioussystems. Using these findings, an empirical model has been developed which can predict the loss of Li{sup +} ions from the pore solution during the hydration period. The proposed model can be used to investigate the effects of mixture parameters on the loss of Li{sup +} ions from the pore solution of cementitioussystem.

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.

This work extends the results of a recently developed theory of a rather complete thermodynamic formalism for discrete-state, continuous-time Markov processes with and without detailed balance. We investigate whether and in what way the thermodynamic structure is invariant in a multiscale stochastic system, that is, whether the relations between thermodynamic functions of state and process variables remain unchanged when the system is viewed at different time scales and resolutions. Our results show that the dynamics on a fast time scale contribute an entropic term to the internal energy function u(S)(x) for the slow dynamics. Based on the conditional free energy u(S)(x), we can then treat the slow dynamics as if the fast dynamics is nonexistent. Furthermore, we show that the free energy, which characterizes the spontaneous organization in a system without detailed balance, is invariant with or without the fast dynamics: The fast dynamics is assumed to reach stationarity instantaneously on the slow time scale; it has no effect on the system's free energy. The same cannot be said for the entropy and the internal energy, both of which contain the same contribution from the fast dynamics. We also investigate the consequences of time-scale separation in connection to the concepts of quasi-stationarity and steady adiabaticity introduced in the phenomenological steady-state thermodynamics. PMID:21599138

This work extends the results of a recently developed theory of a rather complete thermodynamic formalism for discrete-state, continuous-time Markov processes with and without detailed balance. We investigate whether and in what way the thermodynamic structure is invariant in a multiscale stochastic system, that is, whether the relations between thermodynamic functions of state and process variables remain unchanged when the system is viewed at different time scales and resolutions. Our results show that the dynamics on a fast time scale contribute an entropic term to the internal energy function uS(x) for the slow dynamics. Based on the conditional free energy uS(x), we can then treat the slow dynamics as if the fast dynamics is nonexistent. Furthermore, we show that the free energy, which characterizes the spontaneous organization in a system without detailed balance, is invariant with or without the fast dynamics: The fast dynamics is assumed to reach stationarity instantaneously on the slow time scale; it has no effect on the system’s free energy. The same cannot be said for the entropy and the internal energy, both of which contain the same contribution from the fast dynamics. We also investigate the consequences of time-scale separation in connection to the concepts of quasi-stationarity and steady adiabaticity introduced in the phenomenological steady-state thermodynamics.

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

We study a two-time-scale system of jump-diffusion stochastic differential equations. We analyze a class of multiscale integration methods for these systems, which, in the spirit of [1], consist of a hybridization between a standard solver for the slow components and short runs for the fast dynamics, which are used to estimate the effect that the fast components have on the slow ones. We obtain explicit bounds for the discrepancy between the results of the multiscale integration method and the slow components of the original system.

This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

Nuclear medicine imaging is a widely used commercial imaging modality which relies on photon detection as the basis of image formation. As a diagnosis tool, it is unique in that it documents organ function and structure. It is a way to gather information that may be otherwise unavailable or require surgery. Practical limitations on imaging time and the amount of activity that can be administered safely to patients are serious impediments to substantial further improvements in nuclear medicine imaging. Hence, improvements of image quality via optimized image processing represent a significant opportunity to advance the state-of-the-art int his field. We present in this paper a new multiscale image restoration method that is concerned with eliminating one of the major sources of error in nuclear medicine imaging, namely Poisson noise, which degrades images in both quantitative and qualitative senses and hinders image analysis and interpretation. The paper then quantitatively evaluates the performances of the proposed method.

The land-atmosphere system is characterized by pronounced land surface heterogeneity and vigorous atmospheric turbulence both covering a wide range of scales. The multiscale surface heterogeneities and multiscale turbulent eddies interact nonlinearly with each other. Understanding these multiscale processes quantitatively is essential to the subgrid parameterizations for weather and climate models. In this paper, we propose a method for surface heterogeneity quantification and turbulence structure identification. The first part of the method is an orthogonal transform in the probability density function (PDF) domain, in contrast to the orthogonal wavelet transforms which are performed in the physical space. As the basis of the whole method, the orthogonal PDF transform (OPT) is used to asymptotically reconstruct the original signals by representing the signal values with multilevel approximations. The "patch" idea is then applied to these reconstructed fields in order to recognize areas at the land surface or in turbulent flows that are of the same characteristics. A patch here is a connected area with the same approximation. For each recognized patch, a length scale is then defined to build the energy spectrum. The OPT and related energy spectrum analysis, as a whole referred to as the orthogonal PDF decomposition (OPD), is applied to two-dimensional heterogeneous land surfaces and atmospheric turbulence fields for test. The results show that compared to the wavelet transforms, the OPD can reconstruct the original signal more effectively, and accordingly, its energy spectrum represents the signal's multiscale variation more accurately. The method we propose in this paper is of general nature and therefore can be of interest for problems of multiscale process description in other geophysical disciplines.

The world will continue consuming fossil fuel within the coming decades to meet its growing energy demand; however, this source must be cleaner through implementation of carbon capture, transport and storage (CCTS). This process is complex and involves multiple phases, owned by different operational companies and stakeholders with different business models and regulatory framework. The objective of this work is to develop a multiscale modeling approach to link process models, post-combustion capture plant model and network design models under an optimization framework in order to design and analyse the cost optimal CO2 infrastructure that match CO2 sources and sinks in capacity and time. The network comprises a number of CO2 sources at fixed locations and a number of potential CO2 storage sites. The decisions to be determined include from which sources it is appropriate to capture CO2 and the cost-optimal degree-of-capture (DOC) for a given source and the infrastructural layout of the CO2 transmission network.

This paper provides a first description of a multiscalesystems modeling approach applied to the congenital birth defect known as the tetralogy of Fallot. The multiscale approach adopted owes a lot to the effort of the world-wide physiome consortium and the work of research groups within the European Union on the Virtual Physiological Human. Both a spatial scale and time scale are used to establish the systems boundaries of the application. The tetralogy of Fallot includes up to four simultaneously occurring anatomic abnormalities that underpin the defect. The use of finite state machines and cellular automata pave the way to understand the processes in time and space that contribute to the defect. PMID:21095902

Biochemical systems are inherently multiscale and stochastic. In microscopic systems formed by living cells, the small numbers of reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA, Gillespie, 1976), a numerical simulation procedure that is essentially exact for chemical systems that are spatially homogeneous or well stirred. Despite recent improvements, as a procedure that simulates every reaction event, the SSA is necessarily inefficient for most realistic problems. There are two main reasons for this, both arising from the multiscale nature of the underlying problem: (1) stiffness, i.e. the presence of multiple timescales, the fastest of which are stable; and (2) the need to include in the simulation both species that are present in relatively small quantities and should be modeled by a discrete stochastic process, and species that are present in larger quantities and are more efficiently modeled by a deterministic differential equation (or at some scale in between). This project has focused on the development of fast and adaptive algorithms, and the fun- damental theory upon which they must be based, for the multiscale simulation of biochemical systems. Areas addressed by this project include: (1) Theoretical and practical foundations for ac- celerated discrete stochastic simulation (tau-leaping); (2) Dealing with stiffness (fast reactions) in an efficient and well-justified manner in discrete stochastic simulation; (3) Development of adaptive multiscale algorithms for spatially homogeneous discrete stochastic simulation; (4) Development of high-performance SSA algorithms.

We develop algorithms built around properties of the transfer operator and Koopman operator which (1) test for possible multiscale dynamics in a given dynamical system, (2) estimate the magnitude of the time-scale separation, and finally (3) distill the reduced slow dynamics on a suitably designed subspace. By avoiding trajectory integration, the developed techniques are highly computationally efficient. We corroborate our findings with numerical simulations of a test problem.

The use of high performance concretes that utilize low water-cement ratios have been promoted for use in infrastructure based on their potential to increase durability and service life because they are stronger and less porous. Unfortunately, these benefits are not always realized due to the susceptibility of high performance concrete to undergo early age cracking caused by shrinkage. This problem is widespread and effects federal, state, and local budgets that must maintain or replace deterioration caused by cracking. As a result, methods to reduce or eliminate early age shrinkage cracking have been investigated. Internal curing is one such method in which a prewetted lightweight sand is incorporated into the concrete mixture to provide internal water as the concrete cures. This action can significantly reduce or eliminate shrinkage and in some cases causes a beneficial early age expansion. Standard laboratory tests have been developed to quantify the shrinkage cracking potential of concrete. Unfortunately, many of these tests may not be appropriate for use with internally cured mixtures and only provide limited amounts of information. Most standard tests are not designed to capture the expansive behavior of internally cured mixtures. This thesis describes the design and implementation of two new testing devices that overcome the limitations of current standards. The first device discussed in this thesis is called the dual ring. The dual ring is a testing device that quantifies the early age restrained shrinkage performance of cementitious mixtures. The design of the dual ring is based on the current ASTM C 1581-04 standard test which utilizes one steel ring to restrain a cementitious specimen. The dual ring overcomes two important limitations of the standard test. First, the standard single ring test cannot restrain the expansion that takes place at early ages which is not representative of field conditions. The dual ring incorporates a second restraining ring

The human cardiovascular system is a closed-loop and complex vascular network with multi-scaled heterogeneous hemodynamic phenomena. Here, we give a selective review of recent progress in macro-hemodynamic modeling, with a focus on geometrical multi-scale modeling of the vascular network, micro-hemodynamic modeling of microcirculation, as well as blood cellular, subcellular, endothelial biomechanics, and their interaction with arterial vessel mechanics. We describe in detail the methodology of hemodynamic modeling and its potential applications in cardiovascular research and clinical practice. In addition, we present major topics for future study: recent progress of patient-specific hemodynamic modeling in clinical applications, micro-hemodynamic modeling in capillaries and blood cells, and the importance and potential of the multi-scale hemodynamic modeling.

Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite

More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a "Noah's Ark" milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multiscale and multiphysics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe three examples calculated using MUSE: the merger of two galaxies, the merger of two evolving stars, and a hybrid N-body simulation. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.

With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will be- come more and more complicated, and more and more ?huge?. The costs for improve- ment and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally(4) variable or uniform resolution in option (5) possibility to run in regional or global mode(6) finite difference in the vertical dis- cretization in option (7) semi-implicit and semi-Lagrangian scheme; (8) height terrain- following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993).

The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

This paper presents an overview of the attitude ground system (AGS) currently under development for the Magnetospheric Multiscale (MMS) mission. The primary responsibilities for the MMS AGS are definitive attitude determination, validation of the onboard attitude filter, and computation of certain parameters needed to improve maneuver performance. For these purposes, the ground support utilities include attitude and rate estimation for validation of the onboard estimates, sensor calibration, inertia tensor calibration, accelerometer bias estimation, center of mass estimation, and production of a definitive attitude history for use by the science teams. Much of the AGS functionality already exists in utilities used at NASA's Goddard Space Flight Center with support heritage from many other missions, but new utilities are being created specifically for the MMS mission, such as for the inertia tensor, accelerometer bias, and center of mass estimation. Algorithms and test results for all the major AGS subsystems are presented here.

Nearly all systems of practical interest are composed of parts assembled across multiple scales. For example, an agrodynamic system is composed of flora and fauna on one scale; soil types, slope, and water runoff on another scale; and management practice and yield on another scale. Or consider an advanced coal-fired power plant: combustion and pollutant formation occurs on one scale, the plant components on another scale, and the overall performance of the power system is measured on another. In spite of this, there are few practical tools for the optimization of multiscalesystems. This paper examines multiscale optimization of systems composed of discrete elements using the plus-one-recall-store (PORS) problem as a test case or study problem for multiscalesystems. From this study, it is found that by recognizing the constraints and patterns present in discrete multiscalesystems, the solution time can be significantly reduced and much more complex problems can be optimized.

Systems biology is an approach to understanding living systems that focuses on modeling diverse types of high-dimensional interactions to develop a more comprehensive understanding of complex phenotypes manifested by the system. High throughput molecular, cellular, and physiologic profiling of populations is coupled with bioinformatic and computational techniques to identify new functional roles for genes, regulatory elements, and metabolites in the context of the molecular networks that define biological processes associated with system physiology. Given the complexity and heterogeneity of asthma and allergic diseases, a systems biology approach is attractive, as it has the potential to model the myriad connections and interdependencies between genetic predisposition, environmental perturbations, regulatory intermediaries, and molecular sequelae that ultimately lead to diverse disease phenotypes and treatment responses across individuals. The increasing availability of high-throughput technologies has enabled system-wide profiling of the genome, transcriptome, epigenome, microbiome, and metabolome, providing fodder for systems biology approaches to examine asthma and allergy at a more holistic level. In this article, we review the technologies and approaches for system-wide profiling as well as their more recent applications to asthma and allergy. We discuss approaches for integrating multiscale data through network analyses and provide perspective on how individually-captured health profiles will contribute to more accurate systems biology views of asthma and allergy. PMID:25468194

enables rational design of CNC-based bionanocomposite materials and systems. Furthermore, the 3D-RISM-KH based multiscale modeling addresses the effect of hemicellulose and lignin composition on nanoscale forces that control cell wall strength towards overcoming plant biomass recalcitrance. It reveals molecular forces maintaining the cell wall structure and provides directions for genetic modulation of plants and pretreatment design to render biomass more amenable to processing. We envision integrated biomass valorization based on extracting and decomposing the non-cellulosic components to low molecular weight chemicals and utilizing the cellulose microfibrils to make CNC. This is an important alternative to approaches of full conversion of lignocellulose to biofuels that face challenges arising from the deleterious impact of cellulose crystallinity on enzymatic processing.

The four Magnetospheric Multiscale (MMS) spacecraft will collect a combined volume of ˜100 gigabits per day of particle and field data. On average, only 4 gigabits of that volume can be transmitted to the ground. To maximize the scientific value of each transmitted data segment, MMS has developed the Science Operations Center (SOC) to manage science operations, instrument operations, and selection, downlink, distribution, and archiving of MMS science data sets. The SOC is managed by the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado and serves as the primary point of contact for community participation in the mission. MMS instrument teams conduct their operations through the SOC, and utilize the SOC's Science Data Center (SDC) for data management and distribution. The SOC provides a single mission data archive for the housekeeping and science data, calibration data, ephemerides, attitude and other ancillary data needed to support the scientific use and interpretation. All levels of data products will reside at and be publicly disseminated from the SDC. Documentation and metadata describing data products, algorithms, instrument calibrations, validation, and data quality will be provided. Arguably, the most important innovation developed by the SOC is the MMS burst data management and selection system. With nested automation and "Scientist-in-the-Loop" (SITL) processes, these systems are designed to maximize the value of the burst data by prioritizing the data segments selected for transmission to the ground. This paper describes the MMS science operations approach, processes and data systems, including the burst system and the SITL concept.

A methodology is described to systematically derive coarse-grained (CG) force fields for molecular liquids from the underlying atomistic-scale forces. The coarse graining of an interparticle force field is accomplished by the application of a force-matching method to the trajectories and forces obtained from the atomistic trajectory and force data for the CG sites of the targeted system. The CG sites can be associated with the centers of mass of atomic groups because of the simplicity in the evaluation of forces acting on these sites from the atomistic data. The resulting system is called a multiscale coarse-grained (MS-CG) representation. The MS-CG method for liquids is applied here to water and methanol. For both liquids one-site and two-site CG representations without an explicit treatment of the long-ranged electrostatics have been derived. In addition, for water a two-site model having the explicit long-ranged electrostatics has been developed. To improve the thermodynamic properties (e.g., pressure and density) for the MS-CG models, the constraint for the instantaneous virial was included into the force-match procedure. The performance of the resulting models was evaluated against the underlying atomistic simulations and experiment. In contrast with existing approaches for coarse graining of liquid systems, the MS-CG approach is general, relies only on the interatomic interactions in the reference atomistic system.

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

The state of the art for computational tools in both computational chemistry and computational materials physics includes many algorithms and functionalities which are implemented again and again. Several projects aim to reduce, eliminate, or avoid this problem. Most such efforts seem to be focused within a particular specialty, either quantum chemistry or materials physics. Multi-scale simulations, by their very nature however, cannot respect that specialization. In simulation of fracture, for example, the energy gradients that drive the molecular dynamics (MD) come from a quantum mechanical treatment that most often derives from quantum chemistry. That “QM” region is linked to a surrounding “CM” region in which potentials yield the forces. The approach therefore requires the integration or at least inter-operation of quantum chemistry and materials physics algorithms. The same problem occurs in “QM/MM” simulations in computational biology. The challenge grows if pattern recognition or other analysis codes of some kind must be used as well. The most common mode of inter-operation is user intervention: codes are modified as needed and data files are managed “by hand” by the user (interactively and via shell scripts). User intervention is however inefficient by nature, difficult to transfer to the community, and prone to error. Some progress (e.g Sethna’s work at Cornell [C.R. Myers et al., Mat. Res. Soc. Symp. Proc., 538(1999) 509, C.-S. Chen et al., Poster presented at the Material Research Society Meeting (2000)]) has been made on using Python scripts to achieve a more efficient level of interoperation. In this communication we present an alternative approach to merging current working packages without the necessity of major recoding and with only a relatively light wrapper interface. The scheme supports communication among the different components required for a given multi-scale calculation and access to the functionalities of those components

We present MUSE, a software framework for tying together existing computational tools for different astrophysical domains into a single multiphysics, multiscale workload. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for a generalized stellar systems workload. MUSE has now reached a "Noah's Ark" milestone, with two available numerical solvers for each domain. MUSE can treat small stellar associations, galaxies and everything in between, including planetary systems, dense stellar clusters and galactic nuclei. Here we demonstrate an examples calculated with MUSE: the merger of two galaxies. In addition we demonstrate the working of MUSE on a distributed computer. The current MUSE code base is publicly available as open source at http://muse.li.

Describing the biomechanical properties of cellular systems, regarded as complex highly viscoelastic materials, is a difficult problem of great conceptual and practical value. Here we present a novel approach, referred to as the Cellular Particle Dynamics (CPD) method, for: (i) quantitatively relating biomechanical properties at the cell level to those at the multicellular and tissue level, and (ii) describing and predicting the time evolution of multicellular systems that undergo biomechanical relaxations. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. Cell and multicellular level biomechanical properties (e.g., viscosity, surface tension and shear modulus) are determined through the combined use of experiments and theory of continuum viscoelastic media. The same biomechanical properties are also ``measured'' computationally by employing the CPD method, the results being expressed in terms of CPD parameters. Once these parameters have been calibrated experimentally, the formalism provides a systematic framework to predict the time evolution of complex multicellular systems during shape-changing biomechanical transformations. By design, the CPD method is rather flexible and most suitable for multiscale modeling of multicellular system. The spatial level of detail of the system can be easily tuned by changing the number of CPs in a cell. Thus, CPD can be used equally well to describe both cell level processes (e.g., the adhesion of two cells) and tissue level processes (e.g., the formation of 3D constructs of millions of cells through bioprinting). Work supported by NSF [FIBR-0526854 and PHY-0957914

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

This presentation will first discuss the interplay between agricultural landscapes and regional hydroclimatology with particular emphasis on the US Corn Belt. Results and experiences from studies underway as part of a multistate project (Making Climate Information Useful 2 Usable- U2U) will be summarized. The presentation will also highlight experiences regarding the different challenges in developing the regional assessment and guidance regarding sustainable futures. Study results will also be compared with findings from other geographical regions where agriculture - climate linkages are stretching the limits of sustainable water use. A vulnerability framework that can be considered for such agriculture - climate - water links will also be presented. The second issue the presentation will discuss relates to the urban land surface feedbacks and efforts underway to guide efforts related to greening as well as regional landuse planning. The complex links between city structures, urban layouts, and regional climate will be synthesized and the framework regarding a decision support system that is being developed will be presented. Salient points of the modeling efforts, data challenges, and the need for linking multiple disciplines will be presented with special focus on droughts and the need for considering complex multiscale coupled interactions within the analysis.

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

An ultrafine cementitious grout having a particle size 90% of which are less than 6 .mu.m in diameter and an average size of about 2.5 .mu.m or less, and preferably 90% of which are less than 5 .mu.m in diameter and an average size of about 2 .mu.m or less containing Portland cement, pumice as a pozzolanic material and superplasticizer in the amounts of about 40 wt. % to about 50 wt. % Portland cement; from about 50 wt. % to about 60 wt. % pumice containing at least 60% amorphous silicon dioxide; and from 0.1 wt. % to about 1.5 wt. % superplasticizer. The grout is mixed with water in the W/CM ratio of about 0.4-0.6/1. The grout has very high strength and very low permeability with good workability. The ultrafine particle sizes allow for sealing of microfractures below 10 .mu.m in width.

An ultrafine cementitious grout in three particle grades containing Portland cement, pumice as a pozzolanic material and superplasticizer in the amounts of about 30 wt. % to about 70 wt. % Portland cement; from about 30 wt. % to about 70 wt. % pumice containing at least 70% amorphous silicon dioxide; and from 1.2 wt. % to about 5.0 wt. % superplasticizer. The superplasticizer is dispersed in the mixing water prior to the addition of dry grout and the W/CM ratio is about 0.4 to 1/1. The grout has very high strength and very low permeability with good workability. The ultrafine particle sizes allow for sealing of microfractures below 10 .mu.m in width.

An ultrafine cementitious grout in three particle grades containing Portland cement, pumice as a pozzolanic material and superplasticizer in the amounts of about 30 wt. % to about 70 wt. % Portland cement; from about 30 wt. % to about 70 wt. % pumice containing at least 70% amorphous silicon dioxide; and from 1.2 wt. % to about 5.0 wt. % superplasticizer. The superplasticizer is dispersed in the mixing water prior to the addition of dry grout and the W/CM ratio is about 0.4 to 1/1. The grout has very high strength and very low permeability with good workability. The ultrafine particle sizes allow for sealing of microfractures below 10 {mu}m in width.

With the advent of more powerful computer systems, theoretical modeling of nanoscale systems has quickly become a vital part of scientific research in a multitude of disciplines. From the understanding of semiconductor devices to describing the mechanistic details of protein interactions, theoretical studies on systems of various scales have provided great insight into how nature behaves in each scenario. While at a macroscopic level the differences between biological and non-biological systems are apparent, the underlying principles that dictate their behavior are quite similar. Indeed, modeling these two distinct classes of systems have similar challenges. In both cases, the system sizes typically correspond to nanometer length scales and due to the lack of periodicity in the system, one needs to study a relatively larger number of atoms in simulations in order to represent their behavior. Nonetheless, systems that are much smaller than what exists in experiment may be used to describe specific properties of interest, such as how system stability scales with varying size or describing a reaction process of a large biological structure through the modeling of only the reaction site and not the entire protein. Thus, it is important to be able to correctly and efficiently model various systems at multiple scales in order to provide proper insight and understanding so models and tools developed in one area could be applied to another discipline. Indeed, lessons learned during the process are quite valuable for the general scheme of multiscale modeling in materials. To facilitate this, we have investigated two separate cases involving the efficient use of multiscale modeling through ab initio density functional theory calculations. For the first half of this work, we investigate the effect of size on the net magnetization of zero dimensional graphene based structures with differing edge states. Currently, we have shown that for zigzag edged triangular graphene

The drift and deformation of sea ice cover is most commonly followed from successive SAR images. The time interval between the images is seldom less than one day which provides rather crude approximation of the motion fields as ice can move tens of kilometers per day. This is particulary so from the viewpoint of operative services, seeking to provide real time information for ice navigating ships and other end users, as leads are closed and opened or ridge fields created in time scales of one hour or less. The ice forecast models are in a need of better temporal resolution for ice motion data as well. We present experiences from a multiscale monitoring system set up to the Bay of Bothnia, the northernmost basin of the Baltic Sea. The basin generates difficult ice conditions every winter while the ports are kept open with the help of an icebreaker fleet. The key addition to SAR imagery is the use of coastal radars for the monitoring of coastal ice fields. An independent server is used to tap the radar signal and process it to suit ice monitoring purposes. This is done without interfering the basic use of the radars, the ship traffic monitoring. About 20 images per minute are captured and sent to the headquarters for motion field extraction, website animation and distribution. This provides very detailed real time picture of the ice movement and deformation within 20 km range. The real time movements are followed in addition with ice drifter arrays, and using AIS ship identification data, from which the translation of ship cannels due to ice drift can be found out. To the operative setup is associated an extensive research effort that uses the data for ice drift model enhancement. The Baltic ice models seek to forecast conditions relevant to ship traffic, especilly hazardous ones like severe ice compression. The main missing link here is downscaling, or the relation of local scale ice dynamics and kinematics to the ice model scale behaviour. The data flow when

The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...

This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

An ultrafine cementitious grout is described having a particle size 90% of which are less than 6 {micro}m in diameter and an average size of about 2.5 {micro}m or less, and preferably 90% of which are less than 5 {micro}m in diameter and an average size of about 2 {micro}m or less containing Portland cement, pumice as a pozzolanic material and superplasticizer in the amounts of about 40 wt. % to about 50 wt. % Portland cement; from about 50 wt. % to about 60 wt. % pumice containing at least 60% amorphous silicon dioxide; and from 0.1 wt. % to about 1.5 wt. % superplasticizer. The grout is mixed with water in the W/CM ratio of about 0.4--0.6/1. The grout has very high strength and very low permeability with good workability. The ultrafine particle sizes allow for sealing of microfractures below 10 {micro}m in width. 4 figs.

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented.

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Multi-scale transforms have been shown to be invaluable tools for image processing. The effectiveness of consequently formulated multi-scale algorithms have practically made them de facto standards for realizing solutions for a broad range of image processing problems. Multi-scale formulations of transforms and algorithms are motivated by the ability of the human visual system (HVS) to extract edge structures at their different scales. Image processing algorithms, consequently, have been developed which alter multi-transform coefficients of images for various means. However, the multi-scale contrasts as defined by these schemes generally not consistent with many other relevant HVS phenomena. Upon reviewing relevant HVS characteristics, new tools which are consistent with these features are presented. Accordingly, new image enhancement, image de-noising, and image fusion algorithms which make use of HVS-inspired multi-scale tools are presented as contributions to each of these fields. In this context, the aim of the presented algorithms is two-fold: The intention is to both consider new multi-scale solutions, as well as to formulate them using perceptually-driven mathematical constructs based on HVS characteristics. In the context of image enhancement, a new set of multi-scale image enhancement algorithms are presented which are able to simultaneously provide both local and global enhancements within a direct enhancement framework. For the purpose of image de-noising, a multi-scale formulation of the non-local-means de-noising algorithm is developed which is shown to both visually and quantitatively outperform existing de-noising approaches. Many algorithms to achieve image fusion based on the presented transforms are presented. One set of algorithms is based on a Parameterized Logarithmic Image Processing model, while another is based on an adaptive similarity-based weighting scheme. The interdependence between the different algorithms considered in this

This paper describes the attitude ground system (AGS) design to be used for support of the Magnetospheric MultiScale (MMS) mission. The AGS exists as one component of the mission operations control center. It has responsibility for validating the onboard attitude and accelerometer bias estimates, calibrating the attitude sensors and the spacecraft inertia tensor, and generating a definitive attitude history for use by the science teams. NASA's Goddard Space Flight Center (GSFC) in Greenbelt, Maryland is responsible for developing the MMS spacecraft, for the overall management of the MMS mission, and for mission operations. MMS is scheduled for launch in 2014 for a planned two-year mission. The MMS mission consists of four identical spacecraft flying in a tetrahedral formation in an eccentric Earth orbit. The relatively tight formation, ranging from 10 to 400 km, will provide coordinated observations giving insight into small-scale magnetic field reconnection processes. By varying the size of the tetrahedron and the orbital semi-major axis and eccentricity, and making use of the changing solar phase, this geometry allows for the study of both bow shock and magnetotail plasma physics, including acceleration, reconnection, and turbulence. The mission divides into two phases for science; these phases will have orbit dimensions of 1.2 x 12 Earth radii in the first phase and 1.2x25 Earth radii in the second in order to study the dayside magnetopause and the nightside magnetotail, respectively. The orbital periods are roughly one day and three days for the two mission phases. Each of the four MMS spacecraft will be spin stabilized at 3 revolutions per minute (rpm), with the spin axis oriented near the ecliptic north pole but tipped approximately 2.5 deg towards the Sun line. The main body of each spacecraft will be an eight-sided platform with diameter of 3.4 m and height of 1.2 m. Several booms are attached to this central core: two axial booms of 14.9 m length, two

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the U.S. Department of Energy (US DOE) Office of Tank Waste and Nuclear Materials Management. The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that help improve understanding and predictions of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. Tools selected for and developed under this program have been used to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to 100 years and longer for operating facilities and longer than 1000 years for waste disposal. The CBP Software Toolbox has produced tangible benefits to the DOE Performance Assessment (PA) community. A review of prior DOE PAs has provided a list of potential opportunities for improving cementitious barrier performance predictions through the use of the CBP software tools. These opportunities include: 1) impact of atmospheric exposure to concrete and grout before closure, such as accelerated slag and Tc-99 oxidation, 2) prediction of changes in K{sub d}/mobility as a function of time that result from changing pH and redox conditions, 3) concrete degradation from rebar corrosion due to carbonation, 4) early age cracking from drying and/or thermal shrinkage and 5) degradation due to sulfate attack. The CBP has already had opportunity to provide near-term, tangible support to ongoing DOE-EM PAs such as the Savannah River Saltstone Disposal Facility (SDF) by providing a sulfate attack analysis that predicts the extent and damage that sulfate ingress will have on the concrete vaults over extended time (i.e., > 1000 years). This analysis is one of the many technical opportunities in cementitious barrier performance that can be addressed by the DOE-EM sponsored CBP

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the U.S. Department of Energy (US DOE) Office of Tank Waste and Nuclear Materials Management. The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that help improve understanding and predictions of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. Tools selected for and developed under this program have been used to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to 100 years and longer for operating facilities and longer than 1000 years for waste disposal. The CBP Software Toolbox has produced tangible benefits to the DOE Performance Assessment (PA) community. A review of prior DOE PAs has provided a list of potential opportunities for improving cementitious barrier performance predictions through the use of the CBP software tools. These opportunities include: 1) impact of atmospheric exposure to concrete and grout before closure, such as accelerated slag and Tc-99 oxidation, 2) prediction of changes in Kd/mobility as a function of time that result from changing pH and redox conditions, 3) concrete degradation from rebar corrosion due to carbonation, 4) early age cracking from drying and/or thermal shrinkage and 5) degradation due to sulfate attack. The CBP has already had opportunity to provide near-term, tangible support to ongoing DOE-EM PAs such as the Savannah River Saltstone Disposal Facility (SDF) by providing a sulfate attack analysis that predicts the extent and damage that sulfate ingress will have on the concrete vaults over extended time (i.e., > 1000 years). This analysis is one of the many technical opportunities in cementitious barrier performance that can be addressed by the DOE-EM sponsored CBP software

Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address this problem, assuming that the evolution of the slow species in the system is well approximated by a Langevin process. It is based on the conditional stochastic simulation algorithm (CSSA) which samples from the conditional distribution of the suitably defined fast variables, given values for the slow variables. In the constrained multiscale algorithm (CMA) a single realization of the CSSA is then used for each value of the slow variable to approximate the effective drift and diffusion terms, in a similar manner to the constrained mean-force computations in other applications such as molecular dynamics. We then show how using the ensuing Fokker-Planck equation approximation, we can in turn approximate average switching times in stochastic chemical systems.

A multi-scale method is utilized to determine some of the constitutive properties of a three component graphite-epoxy-nanotube system. This system is of interest because carbon nanotubes have been proposed as stiffening and toughening agents in the interlaminar regions of carbon fiber/epoxy laminates. The multi-scale method uses molecular dynamics simulation and equivalent-continuum modeling to compute three of the elastic constants of the graphite-epoxy-nanotube system: C11, C22, and C33. The 1-direction is along the nanotube axis, and the graphene sheets lie in the 1-2 plane. It was found that the C11 is only 4% larger than the C22. The nanotube therefore does have a small, but positive effect on the constitutive properties in the interlaminar region.

The Cementitious Barriers Partnership (CBP) was initiated to reduce risk and uncertainties in the performance assessments that directly impact U.S. Department of Energy (DOE) environmental cleanup and closure programs. The CBP is supported by the DOE Office of Environmental Management (DOE-EM) and has been specifically addressing the following critical EM program needs: (i) the long-term performance of cementitious barriers and materials in nuclear waste disposal facilities and (ii) increased understanding of contaminant transport behavior within cementitious barrier systems to support the development and deployment of adequate closure technologies. To accomplish this, the CBP has two initiatives: (1) an experimental initiative to increase understanding of changes in cementitious materials over long times (> 1000 years) over changing conditions and (2) a modeling initiative to enhance and integrate a set of computational tools validated by laboratory and field experimental data to improve understanding and prediction of the long-term performance of cementitious barriers and waste forms used in nuclear applications. In FY10, the CBP developed the initial phase of an integrated modeling tool that would serve as a screening tool which could help in making decisions concerning disposal and tank closure. The CBP experimental programs are underway to validate this tool and provide increased understanding of how CM changes over time and under changing conditions. These initial CBP products that will eventually be enhanced are anticipated to reduce the uncertainties of current methodologies for assessing cementitious barrier performance and increase the consistency and transparency of the DOE assessment process. These tools have application to low activity waste forms, high level waste tank closure, D&D and entombment of major nuclear facilities, landfill waste acceptance criteria, and in-situ grouting and immobilization of vadose zone contamination. This paper summarizes

A self-degradable alkali-activated cementitious material consisting of a sodium silicate activator, slag, Class C fly ash, and sodium carboxymethyl cellulose (CMC) additive was formulated as one dry mix component, and we evaluated its potential in laboratory for use as a temporary sealing material for Enhanced Geothermal System (EGS) wells. The self-degradation of alkali-activated cementitious material (AACM) occurred, when AACM heated at temperatures of {ge}200 C came in contact with water. We interpreted the mechanism of this water-initiated self-degradation as resulting from the in-situ exothermic reactions between the reactants yielded from the dissolution of the non-reacted or partially reacted sodium silicate activator and the thermal degradation of the CMC. The magnitude of self-degradation depended on the CMC content; its effective content in promoting degradation was {ge}0.7%. In contrast, no self-degradation was observed from CMC-modified Class G well cement. For 200 C-autoclaved AACMs without CMC, followed by heating at temperatures up to 300 C, they had a compressive strength ranging from 5982 to 4945 psi, which is {approx}3.5-fold higher than that of the commercial Class G well cement; the initial- and final-setting times of this AACM slurry at 85 C were {approx}60 and {approx}90 min. Two well-formed crystalline hydration phases, 1.1 nm tobermorite and calcium silicate hydrate (I), were responsible for developing this excellent high compressive strength. Although CMC is an attractive, as a degradation-promoting additive, its addition to both the AACM and the Class G well cement altered some properties of original cementitious materials; among those were an extending their setting times, an increasing their porosity, and lowering their compressive strength. Nevertheless, a 0.7% CMC-modified AACM as self-degradable cementitious material displayed the following properties before its breakdown by water; {approx}120 min initial- and {approx}180 min final

This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.

Multi-scale measurement systems utilise multiple sensors which differ in resolution and measurement field to pursue an active exploration strategy. The different sensor scales are linked by indicator algorithms for further measurement initiation. A major advantage of this strategy is a reduction of the conflict between resolution, time and field. This reduction is achieved by task specific conditioning of sensors, indicator algorithms and actuators using suitable uncertainty models. This contribution is focused on uncertainty models of sensors and actuators using the example of a prototype multi-scale measurement system. The influence of the sensor parameters, object characteristics and measurement conditions on the measurement reliability is investigated exemplary for the middle-scale sensor, a confocal microscope.

In this paper, the Hilbert-Huang transform method and time delay embedding method are applied to multiscale dynamic analysis on the time series of silicon content in hot metal collected from a medium-sized blast furnace with the inner volume of 2500 m3. The results provide clear evidence of multiscale features in blast furnace ironmaking process. Ten intrinsic mode functions (IMFs) are decomposed from the silicon content time series; the presence of noninteger fractal dimension, positive finite Kolmogorov entropy, and positive finite maximum Lyapunov exponent are found in some IMF components. In addition, the coupling of subscale structures of blast furnace system is studied using the dimension of interaction dynamics and a robust algorithm for detecting interdependence. It is found that IMF(3) is the main driver in the coupling system IMF(2) and IMF(3) while for the coupling system IMF(3) and IMF(4) neither subsystem can act as the driver. All these provide a guideline for studying blast furnace ironmaking process with multiscale theory and methods, and may open way for more candidate tools to model and control blast furnace system in the future.

In this paper, the Hilbert-Huang transform method and time delay embedding method are applied to multiscale dynamic analysis on the time series of silicon content in hot metal collected from a medium-sized blast furnace with the inner volume of 2500 m3. The results provide clear evidence of multiscale features in blast furnace ironmaking process. Ten intrinsic mode functions (IMFs) are decomposed from the silicon content time series; the presence of noninteger fractal dimension, positive finite Kolmogorov entropy, and positive finite maximum Lyapunov exponent are found in some IMF components. In addition, the coupling of subscale structures of blast furnace system is studied using the dimension of interaction dynamics and a robust algorithm for detecting interdependence. It is found that IMF(3) is the main driver in the coupling system IMF(2) and IMF(3) while for the coupling system IMF(3) and IMF(4) neither subsystem can act as the driver. All these provide a guideline for studying blast furnace ironmaking process with multiscale theory and methods, and may open way for more candidate tools to model and control blast furnace system in the future. PMID:20887042

Despite advancements in technology and science over the last century, the mechanisms underlying Wolff's law-bone structure adaptation in response to physical stimuli-remain poorly understood, limiting the ability to effectively treat and prevent skeletal diseases. A challenge to overcome in the study of the underlying mechanisms of this principle is the multiscale nature of mechanoadaptation. While there exist in silico systems that are capable of studying across these scales, experimental studies are typically limited to interpretation at a single dimension or time point. For instance, studies of single-cell responses to defined physical stimuli offer only a limited prediction of the whole bone response, while overlapping pathways or compensatory mechanisms complicate the ability to isolate critical targets in a whole animal model. Thus, there exists a need to develop experimental systems capable of bridging traditional experimental approaches and informing existing multiscale theoretical models. The purpose of this article is to review the process of mechanoadaptation and inherent challenges in studying its underlying mechanisms, discuss the limitations of traditional experimental systems in capturing the many facets of this process and highlight three multiscale experimental systems which bridge traditional approaches and cover relatively understudied time and length scales in bone adaptation. PMID:26855756

In an effort to provide a state-of-the-science air quality modeling capability, US EPA has developed a new comprehensive and flexible Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. The authors demonstrate CMAQ simulations for a high ozone episode in the northeastern US during 12-15 July 1995 and discuss meteorological issues important for modeling of urban air quality.

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

Strategically embedding graphite meshes in a compliant cementitious matrix produces a composite material with relatively high tension and compressive properties as compared to steel-reinforced structures fabricated from a standard concrete mix. Although these composite systems are somewhat similar, the methods used to analyze steel-reinforced composites often fail to characterize the behavior of their more advanced graphite-reinforced counterparts. This Technical Memorandum describes some of the analytical methods being developed to determine the deflections and stresses in graphite-reinforced cementitious composites. It is initially demonstrated that the standard transform section method fails to provide accurate results when the elastic moduli ratio exceeds 20. An alternate approach is formulated by using the rule of mixtures to determine a set of effective material properties for the composite. Tensile tests are conducted on composite samples to verify this approach. When the effective material properties are used to characterize the deflections of composite beams subjected to pure bending, an excellent agreement is obtained. Laminated composite plate theory is investigated as a means for analyzing even more complex composites, consisting of multiple graphite layers oriented in different directions. In this case, composite beams are analyzed using the laminated composite plate theory with material properties established from tensile tests. Then, finite element modeling is used to verify the results. Considering the complexity of the samples, a very good agreement is obtained.

Method for the production of cementitious compositions and aggregate derivatives of said compositions, and cementitious compositions and aggregates produced by said method, wherein fluidized bed combustion residue and pozzolanic material, such as pulverized coal combustion system fly ash, are incorporated in a cementitious mix. The mix is cast into desired shape and cured. If desired, the shape may then be crushed so as to result in a fluidized bed combustion residue-fly ash aggregate material or the shape may be used by itself.

The Cementitious Barriers Project (CBP) is a multidisciplinary cross cutting project initiated by the US Department of Energy (DOE) to develop a reasonable and credible set of tools to improve understanding and prediction of the structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The period of performance is >100 years for operating facilities and > 1000 years for waste management. The CBP has defined a set of reference cases to provide the following functions: (1) a common set of system configurations to illustrate the methods and tools developed by the CBP, (2) a common basis for evaluating methodology for uncertainty characterization, (3) a common set of cases to develop a complete set of parameter and changes in parameters as a function of time and changing conditions, and (4) a basis for experiments and model validation, and (5) a basis for improving conceptual models and reducing model uncertainties. These reference cases include the following two reference disposal units and a reference storage unit: (1) a cementitious low activity waste form in a reinforced concrete disposal vault, (2) a concrete vault containing a steel high-level waste tank filled with grout (closed high-level waste tank), and (3) a spent nuclear fuel basin during operation. Each case provides a different set of desired performance characteristics and interfaces between materials and with the environment. Examples of concretes, grout fills and a cementitious waste form are identified for the relevant reference case configurations.

The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive, aerospace, ship-making, construction, and pharmaceutical industries. However, how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area. The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes. This research centers on the development of a comprehensive multiscale computational methodology and a computer-aided tool set that can facilitate multifunctional nanocoating design and application from novel function envisioning and idea refinement, to knowledge discovery and design solution derivation, and further to performance testing in industrial applications and life cycle analysis. The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials, product and associated manufacturing processes covering a wide range of length and time scales. Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled. The tight integration of different methods and theories at individual scales allows the prediction of macroscopic coating performance from the fundamental molecular behavior. Goal-oriented design is also pursued by integrating additional methods for bio-inspired dynamic optimization and computational task management that can be implemented in a hierarchical computing architecture. Furthermore, multiscalesystems methodologies are developed to achieve the best possible material application towards sustainable manufacturing. Automotive coating manufacturing, that involves paint spay and

The object of this work is to simulate the dynamic fracture propagation in fibre-reinforced cementitious composites, in particular, in steel fibre reinforced concrete (SFRC). Beams loaded in a three-point bend configuration through a drop-weight impact device are considered. A single cohesive crack is assumed to propagate at the middle section; the opening of this crack is governed by a rate-dependent cohesive law; the fibres around the fracture plane are explicitly represented through truss elements. The fibre pull-out behaviour is depicted by an equivalent constitutive law, which is obtained from an analytical load-slip curve. The obtained load-displacement curves and crack propagation velocities are compared with their experimental counterparts. The good agreement with experimental data testifies to the feasibility of the proposed methodology and paves the way to its application in a multi-scale framework.

Systems whose dynamics result from the existence of a wide variety of time and length scales frequently exhibit slow relaxation behavior, manifested through the aging compartment of the correlations and the nonexponential decay of the response function. Experiments performed in systems such as amorphous polymers and supercooled liquids and glasses seem to indicate that these systems undergo, in general, non-Markovian and nonstationary dynamics. Hence, in this contribution, we present a dynamical description of slow relaxation systems based on a generalization of Onsager's theory to nonequilibrium aging states. By assuming the existence of a local quasi-equilibrium state characterized by a nonstationary probability distribution the entropy of the system is expressed in terms of the conditional probability density by means of the Gibbs entropy postulate. Thus, by taking into account probability conservation and the rules of nonequilibrium thermodynamics, the generalized Fokker-Planck equation is derived.

Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-levelmore » dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.« less

Global environmental change, growing anthropogenic influence, and increasing globalisation of society have made it clear that disaster vulnerability and resilience of communities cannot be understood without knowledge on the broader social-ecological system in which they are embedded. We propose a framework for diagnosing community resilience to disasters, as a form of disturbance to social-ecological systems, with feedbacks from the local to the global scale. Inspired by iterative multi-scale analysis employed by Resilience Alliance, the related socio-ecological systems framework of Ostrom, and the sustainable livelihood framework, we developed a multi-tier framework for thinking of communities as multi-scale social-ecological systems and analyzing communities' disaster resilience and also general resilience. We highlight the cross-scale influences and feedbacks on communities that exist from lower (e.g., household) to higher (e.g., regional, national) scales. The conceptual framework is then applied to a real-world resilience assessment situation, to illustrate how key components of socio-ecological systems, including natural hazards, natural and man-made environment, and community capacities can be delineated and analyzed.

This paper presents a new control strategy which unifies the direct and indirect multi-scale control schemes via a double-loop control structure. This unified control strategy is proposed for controlling a class of highly nonminimum-phase processes having both integrating and unstable modes. This type of systems is often encountered in fed-batch fermentation processes which are very difficult to stabilize via most of the existing well-established control strategies. A systematic design procedure is provided where its applicability is demonstrated via a numerical example.

The foremost challenge in parameterizing convective clouds and cloud systems in large-scale models are the many coupled dynamical and physical processes that interact over a wide range of scales, from microphysical scales to the synoptic and planetary scales. This makes the comprehension and representation of convective clouds and cloud systems one of the most complex scientific problems in Earth science. During the past decade, the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) has pioneered the use of single-column models (SCMs) and cloud-resolving models (CRMs) for the evaluation of the cloud and radiation parameterizations in general circulation models (GCMs; e.g., GEWEX Cloud System Science Team 1993). These activities have uncovered many systematic biases in the radiation, cloud and convection parameterizations of GCMs and have led to the development of new schemes (e.g., Zhang 2002; Pincus et al, 2003; Zhang and Wu 2003; Wu et al. 2003; Liang and Wu 2005; Wu and Liang 2005, and others). Comparisons between SCMs and CRMs using the same large-scale forcing derived from field campaigns have demonstrated that CRMs are superior to SCMs in the prediction of temperature and moisture tendencies (e.g., Das et al. 1999; Randall et al 2003b; Xie et al. 2005).

Computational Homology in Fluids: M. Schatz, K. Mischaikow. This effort focused on characterizing both the structure and dynamics of complex spatio-temporal flows that arise in thermal convection. Microstructure Characterization: T. Wanner, K. Mischaikow. We extended our previous work on studying the time evolution of patterns associated with phase separation in conserved concentration fields. Probabilistic Homology Validation: W. Kalies, T. Wanner, K. Mischaikow. Our above mentioned work on microstructure characterization is based on numerically studying the homology of certain sublevel sets of a function, whose evolution is described by deterministic or stochastic evolution equations. Computational Homology and Dynamics: W. Kalies, T. Wanner, K. Mischaikow. Topological methods can be used to rigorously describe the dynamics of nonlinear systems. We are approaching this problem from several perspectives and through a variety of systems. Stress Networks in Polycrystals: T. Wanner. Together with E. Fuller (NIST) and D. Saylor (FDA) we have characterized stress networks in polycrystals. This part of the project is aimed at developing homological metrics which can aid in distinguishing not only microstructures, but also derived mechanical response fields. Microstructure-Controlled Drug Release: K. Mischaikow, T. Wanner. This part of the project is concerned with the development of topological metrics in the context of controlled drug delivery systems, such as drug-eluting stents. We are particularly interested in developing metrics which can be used to link the processing stage to the resulting microstructure, and ultimately to the achieved system response in terms of drug release profiles. Microstructure of Fuel Cells: W. Kalies, K. Mischaikow. In collaboration with P. Voorhees (Northwestern Univ.) and M. Gameiro (Rutgers) we have been using our computational homology software to analyze the topological structure of the void, metal and ceramic components of a Solid

Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement. PMID:25429262

Dynamical systems with multiple, hierarchically long-delayed feedback are introduced and studied extending our previous work [Yanchuk and Giacomelli, Phys. Rev. Lett. 112, 174103 (2014)]. Focusing on the phenomenological model of a Stuart-Landau oscillator with two feedbacks, we show the multiscale properties of its dynamics and demonstrate them by means of a space-time representation. For sufficiently long delays, we derive a normal form describing the system close to the destabilization. The space and temporal variables, which are involved in the space-time representation, correspond to suitable time scales of the original system. The physical meaning of the results, together with the interpretation of the description at different scales, is presented and discussed. In particular, it is shown how this representation uncovers hidden multiscale patterns such as spirals or spatiotemporal chaos. The effect of the delay size and the features of the transition between small and large delays is also analyzed. Finally, we comment on the application of the method and on its extension to an arbitrary, but finite, number of delayed feedback terms. PMID:26565300

Many natural and technological systems fail to adapt to changing external conditions and move to a different state if the conditions vary too fast. Such 'non-adiabatic' processes are ubiquitous, but little understood. We identify these processes with a new nonlinear phenomenon-an intricate threshold where a forced system fails to adiabatically follow a changing stable state. In systems with multiple time scales, we derive existence conditions that show such thresholds to be generic, but non-obvious, meaning they cannot be captured by traditional stability theory. Rather, the phenomenon can be analysed using concepts from modern singular perturbation theory: folded singularities and canard trajectories, including composite canards. Thus, non-obvious thresholds should explain the failure to adapt to a changing environment in a wide range of multi-scalesystems including: tipping points in the climate system, regime shifts in ecosystems, excitability in nerve cells, adaptation failure in regulatory genes and adiabatic switching in technology. PMID:25294963

Many natural and technological systems fail to adapt to changing external conditions and move to a different state if the conditions vary too fast. Such ‘non-adiabatic’ processes are ubiquitous, but little understood. We identify these processes with a new nonlinear phenomenon—an intricate threshold where a forced system fails to adiabatically follow a changing stable state. In systems with multiple time scales, we derive existence conditions that show such thresholds to be generic, but non-obvious, meaning they cannot be captured by traditional stability theory. Rather, the phenomenon can be analysed using concepts from modern singular perturbation theory: folded singularities and canard trajectories, including composite canards. Thus, non-obvious thresholds should explain the failure to adapt to a changing environment in a wide range of multi-scalesystems including: tipping points in the climate system, regime shifts in ecosystems, excitability in nerve cells, adaptation failure in regulatory genes and adiabatic switching in technology. PMID:25294963

Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings. PMID:26019013

- We extended our previous work on studying the time evolution of patterns associated with phase separation in conserved concentration fields. (6) Probabilistic Homology Validation - work on microstructure characterization is based on numerically studying the homology of certain sublevel sets of a function, whose evolution is described by deterministic or stochastic evolution equations. (7) Computational Homology and Dynamics - Topological methods can be used to rigorously describe the dynamics of nonlinear systems. We are approaching this problem from several perspectives and through a variety of systems. (8) Stress Networks in Polycrystals - we have characterized stress networks in polycrystals. This part of the project is aimed at developing homological metrics which can aid in distinguishing not only microstructures, but also derived mechanical response fields. (9) Microstructure-Controlled Drug Release - This part of the project is concerned with the development of topological metrics in the context of controlled drug delivery systems, such as drug-eluting stents. We are particularly interested in developing metrics which can be used to link the processing stage to the resulting microstructure, and ultimately to the achieved system response in terms of drug release profiles. (10) Microstructure of Fuel Cells - we have been using our computational homology software to analyze the topological structure of the void, metal and ceramic components of a Solid Oxide Fuel Cell.

- We extended our previous work on studying the time evolution of patterns associated with phase separation in conserved concentration fields. (6) Probabilistic Homology Validation - work on microstructure characterization is based on numerically studying the homology of certain sublevel sets of a function, whose evolution is described by deterministic or stochastic evolution equations. (7) Computational Homology and Dynamics - Topological methods can be used to rigorously describe the dynamics of nonlinear systems. We are approaching this problem from several perspectives and through a variety of systems. (8) Stress Networks in Polycrystals - we have characterized stress networks in polycrystals. This part of the project is aimed at developing homological metrics which can aid in distinguishing not only microstructures, but also derived mechanical response fields. (9) Microstructure-Controlled Drug Release - This part of the project is concerned with the development of topological metrics in the context of controlled drug delivery systems, such as drug-eluting stents. We are particularly interested in developing metrics which can be used to link the processing stage to the resulting microstructure, and ultimately to the achieved system response in terms of drug release profiles. (10) Microstructure of Fuel Cells - we have been using our computational homology software to analyze the topological structure of the void, metal and ceramic components of a Solid Oxide Fuel Cell.

Multiphysics problems often involve components whose macroscopic dynamics is driven by microscopic random fluctuations. The fidelity of simulations of such systems depends on their ability to propagate these random fluctuations throughout a computational domain, including subdomains represented by deterministic solvers. When the constituent processes take place in nonoverlapping subdomains, system behavior can be modeled via a domain-decomposition approach that couples separate components at the interfaces between these subdomains. Its coupling algorithm has to maintain a stable and efficient numerical time integration even at high noise strength. We propose a conservative domain-decomposition algorithm in which tight coupling is achieved by employing either Picard's or Newton's iterative method. Coupled diffusion equations, one of which has a Gaussian white-noise source term, provide a computational testbed for analysis of these two coupling strategies. Fully-converged ("implicit") coupling with Newton's method typically outperforms its Picard counterpart, especially at high noise levels. This is because the number of Newton iterations scales linearly with the amplitude of the Gaussian noise, while the number of Picard iterations can scale superlinearly. At large time intervals between two subsequent inter-solver communications, the solution error for single-iteration ("explicit") Picard's coupling can be several orders of magnitude higher than that for implicit coupling. Increasing the explicit coupling's communication frequency reduces this difference, but the resulting increase in computational cost can make it less efficient than implicit coupling at similar levels of solution error, depending on the communication frequency of the latter and the noise strength. This trend carries over into higher dimensions, although at high noise strength explicit coupling may be the only computationally viable option.

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique.

With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will become more and more complicated, and more and more "huge". The costs for improvement and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally; (4) variable or uniform resolution in option; (5) possibility to run in regional or global mode; (6) finite difference in the vertical discretization in option; (7) semi-implicit and semi - Lagrangian scheme; (8) height terrain-following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993). Key Words: numerical weather prediction, grid point model, non-hydrostatic, variable resolution, vertical spectral formulation

Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -É linear eddy-viscosity model, k - É non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523

This paper studies the statistics and tectonism of a multiscale natural fracture system in limestone. The fracture network exhibits a self-similar characteristic with a correlation between its power law length exponent a and fractal dimension D, i.e., a ≈ D + 1. Contradicting the scale-invariant connectivity of idealized self-similar systems, the percolation state of trace patterns mapped at different scales and localities of the study area varies significantly, from well to poorly connected. A tectonic interpretation based on a polyphase fracture network evolution history is proposed to explain this discrepancy. We present data to suggest that the driving force for fracture formation may be dissipated at the end of a tectonic event when the system becomes connected. However, the "effective" connectivity can successively be reduced by cementation of early fractures and reestablished by subsequent cracking, rendering a variable "apparent" connectivity that can be significantly above the percolation threshold.

The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...

A model has been developed for the sorption of radioelements onto cementitious materials based on the diffuse-layer modeling approach. The model assumes that silicon sites (>SiOH) and calcium sites (>CaOH) dominate the surface chemistry and the sorption of radioelements onto the cementitious materials. Both types of site may undergo surface protonation and deprotonation reactions. Cement-based systems vary greatly in their chemistry depending on their calcium-to-silicon molar ratio, and the corresponding variation in the surface chemistry has been incorporated by allowing sorption of calcium ions onto silicon sites. This process results in a change from a silica-type surface, at very low calcium-silicon ratios, to a calcium hydroxide-type surface for high-calcium cement-based materials. The predicted variation in the surface chemistry is consistent with literature data on measured zeta potentials of cements. The model has been applied successfully to describe the sorption of simple caesium and iodide ions at varying calcium-silicon ratios. In a Nirex repository for low and intermediate level wastes, a high-calcium cementitious backfill would be specified. This model has allowed a consistent interpretation of experimental data for sorption of key radioelements, including uranium and plutonium, onto the backfill, under saline and non-saline conditions.

Finely ground glass has the potential for pozzolanic reactivity and can serve as a supplementary cementitious material (SCM). Glass reaction kinetics depends on both temperature and glass composition. Uniform composition, amorphous nature, and high silica content of glass make ground glass an ideal material for studying the effects of glass type and particle size on reactivity at different temperature. This study focuses on how three narrow size ranges of clear and green glass cullet, 63--75 mum, 25--38 mum, and smaller than 25 mum, as well as combination of glass types and particle sizes affects the microstructure and performance properties of cementitioussystems containing glass cullet as a SCM. Isothermal calorimetry, chemical shrinkage, thermogravimetric analysis (TGA), quantitative analysis of X-ray diffraction (XRD), and analysis of scanning electron microscope (SEM) images in backscattered (BS) mode were used to quantify the cement reaction kinetics and microstructure. Additionally, compressive strength and water sorptivity experiments were performed on mortar samples to correlate reactivity of cementitious materials containing glass to the performance of cementitious mixtures. A recently-developed modeling platform called "muic the model" was used to simulated pozzolanic reactivity of single type and fraction size and combined types and particle sizes of finely ground glass. Results showed that ground glass exhibits pozzolanic properties, especially when particles of clear and green glass below 25 mum and their combination were used at elevated temperatures, reflecting that glass cullet is a temperature-sensitive SCM. Moreover, glass composition was seen to have a large impact on reactivity. In this study, green glass showed higher reactivity than clear glass. Results also revealed that the simultaneous effect of sizes and types of glass cullet (surface area) on the degree of hydration of glass particles can be accounted for through a linear addition

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

In this white paper, a road map is presented to establish a multiphysics simulation capability for the design and optimization of sensor systems that incorporate nanomaterials and technologies. The Engineering Directorate's solid/fluid mechanics and electromagnetic computer codes will play an important role in both multiscale modeling and integration of required physics issues to achieve a baseline simulation capability. Molecular dynamic simulations performed primarily in the BBRP, CMS and PAT directorates, will provide information for the construction of multiscale models. All of the theoretical developments will require closely coupled experimental work to develop material models and validate simulations. The plan is synergistic and complimentary with the Laboratory's emerging core competency of multiscale modeling. The first application of the multiphysics computer code is the simulation of a ''simple'' biological system (protein recognition utilizing synthesized ligands) that has a broad range of applications including detection of biological threats, presymptomatic detection of illnesses, and drug therapy. While the overall goal is to establish a simulation capability, the near-term work is mainly focused on (1) multiscale modeling, i.e., the development of ''continuum'' representations of nanostructures based on information from molecular dynamics simulations and (2) experiments for model development and validation. A list of LDRDER proposals and ongoing projects that could be coordinated to achieve these near-term objectives and demonstrate the feasibility and utility of a multiphysics simulation capability is given.

An analytic multiscale expression is derived that yields conditions for effective liquid lubrication of oscillating contacts via surface flow over multiple time and length scales. The expression is a logistics function that depends on two quantities, the fraction of lubricant removed at each contact and a scaling parameter given by the logarithm of the ratio of the contact area to the product of the lubricant diffusion coefficient and the cycle time. For industrial machines the expression confirms the need for an oil mist. For magnetic disk drives, the expression predicts that existing lubricants are sufficient for next-generation data storage. For micro-electrical-mechanical systems, the expression predicts that a bound + mobile lubricant composed of tricresyl phosphate on an octadecyltrichlorosilane self-assembled monolayer will be effective only for temperatures greater than approximately 200 K and up to approximately MHz oscillation frequencies. PMID:17661501

We consider here a dataset from an Eulerian automated system, located on the coastal area of the French side of the English Channel (Boulogne-sur-Mer), called MAREL Carnot, operated by IFREMER (France). This system records more than 15 physico-chemical parameters at 20 minutes intervals, and at the constant depth of -1,5m whatever the tidal range. Our study focuses on the period 2004 to 2011. The objective of this study is to have a better understanding of the bloom fluorescence multiscale dynamics, as regards the coastal area of English Channel and possible influence of temperature on this dynamics. Annual blooms are visible, superposed to multiscale fluctuations. The probability density function (PDF) of the fluorescence time series very nicely obeys a power law with slope -2. The PDF for annual portions obeys also power laws, with slopes which are related to the annual average. Empirical mode decomposition (EMD) is used to study the dynamics and display the power spectrum, which will be linked with these dynamics. EMD method is also used to extract a trend and isolate the blooms from the high frequency dynamics. We show that the high frequency part of the fluorescence dynamics has a very large variance during bloom events, compared to normal conditions. We also show that there is a link between the mean winter temperature and the strength of bloom next spring. These results contribute to statistically characterize the bloom dynamics and extract some possible universal relations. Keywords: English Channel; Autonomous monitoring; Power spectra; EMD method; Probability density functions; Power laws.

Among the scenarios in the Decadal Survey (DS) Missions, the advanced data processing group at the ESTO AIST PI workshop identified "Extreme Event Warning" and "Climate Projections" as two of the top priority scenarios. Recently, we (e.g., Shen et al., 2010a,b; 2011a,b) have made attempt of addressing the first by successfully developing the NASA Coupled Advanced global multiscale Modeling and concurrent Visualization systems (CAMVis) on NASA supercomputers, and demonstrating a great potential for extending the lead time (from 5~7 days up to 20 days) of tropical cyclone (TC) prediction with improved multi-scale interactions between a TC with large-scale environmental conditions such as African Easterly Waves (AEWs), and Madden Julian Oscillation (MJOs). In order to increase our confidence in long-term TC prediction and thus TC climate projection, the predictive relationships between large-scale tropical waves and TC formation need to be further examined and verified with massive model and satellite data sets. To achieve this goal, we have conducted multiscale analysis to study the TC genesis processes, accompanied downscaling (from large-scale events) and upscaling (from small-scale events) processes, and their subsequent non-linear interactions. In this study, we first illustrate the complicated multi-scale interactions during TC genesis with our newly-developed 3D streamline packages in the NASA CAMVis system. With selected cases that include twin TCs in 2002, TC Nargis (2008) and hurricane Helene (2006), we will show that the CAMVis can provide a detailed (zoomed-in) view on hurricane physical processes and an integrative (zoomed-out) view on its interactions with environmental conditions. In the end of talk, we will discuss our future work in multiscale analysis with the Hilbert Huang Transform and improved ensemble empiric mode decomposition.

We present a global, closed-loop, multiscale mathematical model for the human circulation including the arterial system, the venous system, the heart, the pulmonary circulation and the microcirculation. A distinctive feature of our model is the detailed description of the venous system, particularly for intracranial and extracranial veins. Medium to large vessels are described by one-dimensional hyperbolic systems while the rest of the components are described by zero-dimensional models represented by differential-algebraic equations. Robust, high-order accurate numerical methodology is implemented for solving the hyperbolic equations, which are adopted from a recent reformulation that includes variable material properties. Because of the large intersubject variability of the venous system, we perform a patient-specific characterization of major veins of the head and neck using MRI data. Computational results are carefully validated using published data for the arterial system and most regions of the venous system. For head and neck veins, validation is carried out through a detailed comparison of simulation results against patient-specific phase-contrast MRI flow quantification data. A merit of our model is its global, closed-loop character; the imposition of highly artificial boundary conditions is avoided. Applications in mind include a vast range of medical conditions. Of particular interest is the study of some neurodegenerative diseases, whose venous haemodynamic connection has recently been identified by medical researchers. PMID:24431098

The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scalesystems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an

The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

A computational model of the entire cardiovascular system is established based on multi-scale modeling, where the arterial tree is described by a one-dimensional model coupled with a lumped parameter description of the remainder. The resultant multi-scale model forms a closed loop, thus placing arterial wave propagation into a global hemodynamic environment. The model is applied to study the global hemodynamic influences of aortic valvular and arterial stenoses located in various regions. Obtained results show that the global hemodynamic influences of the stenoses depend strongly on their locations in the arterial system, particularly, the characteristics of hemodynamic changes induced by the aortic valvular and aortic stenoses are pronounced, which imply the possibility of noninvasively detecting the presence of the stenoses from peripheral pressure pulses. The variations in aortic pressure/flow pulses with the stenoses play testimony to the significance of modeling the entire cardiovascular system in the study of arterial diseases. PMID:19198911

We describe a technique for the efficient computation of the dominant-scale dynamics of a fluid system when only a high-fidelity simulation is available. Such a technique is desirable when governing equations for the dominant scales are unavailable, when model reduction is impractical, or when the original high-fidelity computation is expensive. We adopt the coarse analysis framework proposed by I. G. Kevrekidis (Comm. Math. Sci. 2003), where a computational superstructure is designed to use short-time, high-fidelity simulations to extract the dominant features for a multiscalesystem. We apply this technique to compute the dominant features of the compressible flow through a planar diffuser. We apply the proper orthogonal decomposition to classify the dominant and subdominant scales of diffuser flows. We derive a coarse projective Adams-Bashforth time integration routine and compute averaged diffuser flows. The results include accurate tracking of the dominant-scale dynamics for a range of parameter values for the computational superstructure. These results demonstrate that coarse analysis methods are useful for solving fluid flow problems of a multiscale nature. In order to elucidate the behavior of coarse analysis techniques, we make comparisons to averaging theory. To this end, we derive governing equations for the average motion of charged particles in a magnetic field in a number of different settings. First, we apply a novel procedure, inspired by WKB theory and Whitham averaging, to average the variational principle. The resulting equations are equivalent to the guiding center equations for charged particle motion; this marks an instance where averaging and variational principles commute. Secondly, we apply Lagrangian averaging techniques, previously applied in fluid mechanics, to derive averaged equations. Making comparisons to the WKB/Whitham derivation allows for the necessary closure of the Lagrangian averaging formulation. We also discuss the

NASA's Magnetospheric Multiscale (MMS) mission, launched in March of 2015, consists of a controlled formation of four spin-stabilized spacecraft in similar highly elliptic orbits reaching apogee at radial distances of 12 and 25 Earth radii (RE) in the first and second phases of the mission. Navigation for MMS is achieved independently on-board each spacecraft by processing Global Positioning System (GPS) observables using NASA Goddard Space Flight Center (GSFC)'s Navigator GPS receiver and the Goddard Enhanced Onboard Navigation System (GEONS) extended Kalman filter software. To our knowledge, MMS constitutes, by far, the highest-altitude operational use of GPS to date and represents a high point of over a decade of high-altitude GPS navigation research and development at GSFC. In this paper we will briefly describe past and ongoing high-altitude GPS research efforts at NASA GSFC and elsewhere, provide details on the design of the MMS GPS navigation system, and present on-orbit performance data from the first phase. We extrapolate these results to predict performance in the second phase orbit, and conclude with a discussion of the implications of the MMS results for future high-altitude GPS navigation, which we believe to be broad and far-reaching.

Background The chemical compound and drug name recognition plays an important role in chemical text mining, and it is the basis for automatic relation extraction and event identification in chemical information processing. So a high-performance named entity recognition system for chemical compound and drug names is necessary. Methods We developed a CHEMDNER system based on mixed conditional random fields (CRF) with word clustering for chemical compound and drug name recognition. For the word clustering, we used Brown's hierarchical algorithm and Skip-gram model based on deep learning with massive PubMed articles including titles and abstracts. Results This system achieved the highest F-score of 88.20% for the CDI task and the second highest F-score of 87.11% for the CEM task in BioCreative IV. The performance was further improved by multi-scale clustering based on deep learning, achieving the F-score of 88.71% for CDI and 88.06% for CEM. Conclusions The mixed CRF model represents both the internal complexity and external contexts of the entities, and the model is integrated with word clustering to capture domain knowledge with PubMed articles including titles and abstracts. The domain knowledge helps to ensure the performance of the entity recognition, even without fine-grained linguistic features and manually designed rules. PMID:25810775

To provide high strength and durability of concrete it is necessary to study the influence of physical and chemical and mechanical principles of dispersed cementitioussystems. The experimental bench was developed to study the influence of electrified surface of cementitious materials on structure formation of hardened cement paste. The test bench allows accelerating the processes of dissolution of cementing materials in water due to influence of electric discharge on their surface. Cement activation with high-voltage corona discharge when AC current is applied allows increasing the ultimate compressive strength of hardened cement paste by 46% at the age of one day and by 20% at the age of 28 days.

NASAs Magnetospheric Multiscale (MMS) mission successfully launched on March 13,2015 (UTC) consists of four identically instrumented spin-stabilized observatories that function as a constellation to study magnetic reconnection in space. The need to maintain sufficiently accurate spatial and temporal formation resolution of the observatories must be balanced against the logistical constraints of executing overly-frequent maneuvers on a small fleet of spacecraft. These two considerations make for an extremely challenging maneuver design problem. This paper focuses on the design elements of a 6-DOF spacecraft attitude control and maneuvering system capable of delivering the high-precision adjustments required by the constellation designers specifically, the design, implementation, and on-orbit performance of the closed-loop formation-class maneuvers that include initialization, maintenance, and re-sizing. The maneuvering control system flown on MMS utilizes a micro-gravity resolution accelerometer sampled at a high rate in order to achieve closed-loop velocity tracking of an inertial target with arc-minute directional and millimeter-per second magnitude accuracy. This paper summarizes the techniques used for correcting bias drift, sensor-head offsets, and centripetal aliasing in the acceleration measurements. It also discusses the on-board pre-maneuver calibration and compensation algorithms as well as the implementation of the post-maneuver attitude adjustments.

Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for (1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with (2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

The vadose zone of karst systems plays an important role on the water dynamics. In particular, temporary perched aquifers can appear in the subsurface due to changes of weather conditions, reduced evapotranspiration and the vertical gradients of porosity and permeability. Although many difficulties are usually encountered when studying karst environments due to their heterogeneities, cave systems offer an outstanding opportunity to investigate vadose zone from the inside. We present a multi-scale study covering two years of hydrogeological and geophysical monitoring of the Lomme Karst System (LKS) located in the Variscan fold-and-thrust belt (Belgium), a region (~ 3000 ha) that shows many karstic networks within Devonian limestone units. Hydrogeological data cover the whole LKS and involve e.g. flows and levels monitoring or tracer tests performed in both vadose and saturated zones. Such data bring valuable information on the hydrological context of the studied area at the catchment scale. Combining those results with geophysical measurements allows validating and imaging them at a smaller scale, with more integrative techniques. Hydrogeophysical measurements are focused on only one cave system of the LKS, at the Rochefort site (~ 40 ha), taking benefit of the Rochefort Cave Laboratory (RCL) infrastructures. In this study, a microgravimetric monitoring and an Electrical Resistivity Tomography (ERT) monitoring are involved. The microgravimetric monitoring consists in a superconducting gravimeter continuously measuring gravity changes at the surface of the RCL and an additional relative gravimeter installed in the underlying cave located 35 meters below the surface. While gravimeters are sensible to changes that occur in both the vadose zone and the saturated zone of the whole cave system, combining their recorded signals allows enhancing vadose zone's gravity changes. Finally, the surface ERT monitoring provide valuable information at the (sub)-meter scale on the

The Magnetospheric Multiscale (MMS) mission, launched on March 13, 2015, is the fourth mission of NASA's Solar Terrestrial Probe program. The MMS mission consists of four identically instrumented observatories that function as a constellation to provide the first definitive study of magnetic reconnection in space. Since it is frequently desirable to isolate electric and magnetic field sensors from stray effects caused by the spacecraft's core-body, the suite of instruments on MMS includes six radial and two axial instrument-booms with deployed lengths ranging from 5-60 meters (see Figure 1). The observatory is spin-stabilized about its positive z-axis with a nominal rate slightly above 3 rev/min (RPM). The spin is also used to maintain tension in the four radial wire-booms. Each observatory's Attitude Control System (ACS) consists of digital sun sensors, star cameras, accelerometers, and mono-propellant hydrazine thrusters-responsible for orbital adjustments, attitude control, and spin adjustments. The sections that follow describe performance requirements, the hardware and algorithms used for 6-DOF estimation, and then similarly for 6-DOF control. The paper concludes with maneuver performance based on both simulated and on-orbit telem.

The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.

A systematic characterization of multivariate dependence at multiple spatio-temporal scales is critical to understanding climate system dynamics and improving predictive ability from models and data. However, dependence structures in climate are complex due to nonlinear dynamical generating processes, long-range spatial and long-memory temporal relationships, as well as low-frequency variability. Here we utilize complex networks to explore dependence in climate data. Specifically, networks constructed from reanalysis-based atmospheric variables over oceans and partitioned with community detection methods demonstrate the potential to capture regional and global dependence structures within and among climate variables. Proximity-based dependence as well as long-range spatial relationships are examined along with their evolution over time, yielding new insights on ocean meteorology. The tools are implicitly validated by confirming conceptual understanding about aggregate correlations and teleconnections. Our results also suggest a close similarity of observed dependence patterns in relative humidity and horizontal wind speed over oceans. In addition, updraft velocity, which relates to convective activity over the oceans, exhibits short spatiotemporal decorrelation scales but long-range dependence over time. The multivariate and multi-scale dependence patterns broadly persist over multiple time windows. Our findings motivate further investigations of dependence structures among observations, reanalysis and model-simulated data to enhance process understanding, assess model reliability and improve regional climate predictions.

In this paper, we describe a mathematical model and a numerical simulation method for the condenser component of a novel two-phase thermosyphon cooling system for power electronics applications. The condenser consists of a set of roll-bonded vertically mounted fins among which air flows by either natural or forced convection. In order to deepen the understanding of the mechanisms that determine the performance of the condenser and to facilitate the further optimization of its industrial design, a multiscale approach is developed to reduce as much as possible the complexity of the simulation code while maintaining reasonable predictive accuracy. To this end, heat diffusion in the fins and its convective transport in air are modeled as 2D processes while the flow of the two-phase coolant within the fins is modeled as a 1D network of pipes. For the numerical solution of the resulting equations, a Dual Mixed-Finite Volume scheme with Exponential Fitting stabilization is used for 2D heat diffusion and convection while a Primal Mixed Finite Element discretization method with upwind stabilization is used for the 1D coolant flow. The mathematical model and the numerical method are validated through extensive simulations of realistic device structures which prove to be in excellent agreement with available experimental data.

The fundamental stochastic-dynamic coevolution laws governing complex coevolutionary systems are introduced in a mathematical physics framework formally unifying nonlinear stochastic physics with fundamental deterministic interaction laws among spatiotemporally distributed processes. The methodological developments are then used to shed light onto fundamental interactions underlying complex spatiotemporal behaviour and emergence in multiscale hydroclimate dynamics. For this purpose, a mathematical physics framework is presented predicting evolving distributions of hydrologic quantities under nonlinearly coevolving geophysical processes. The functional formulation is grounded on first principles regulating the dynamics of each system constituent and their interactions, therefore its applicability is general and data-independent, not requiring local calibrations. Moreover, it enables the dynamical estimation of hydroclimatic variations in space and time from knowledge at different spatiotemporal conditions, along with the associated uncertainties. This paves the way for a robust physically based prediction of hydroclimatic changes in unsupervised areas (e.g. ungauged basins). Validation is achieved by producing, with the mathematical physics framework, a comprehensive spatiotemporal legacy consistent with the observed distributions along with their statistic-dynamic relations. The similarity between simulated and observed distributions is further assessed with novel robust nonlinear information-theoretic diagnostics. The present study brings to light emerging signatures of structural change in hydroclimate dynamics arising from nonlinear synergies across multiple spatiotemporal scales, and contributes to a better dynamical understanding and prediction of spatiotemporal regimes, transitions, structural changes and extremes in complex coevolutionary systems. This study further sheds light onto a diversity of emerging properties from harmonic to hyper-chaotic in general

The objective of this study was to measure technetium ({sup 99}Tc) sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. {sup 99}Tc(VII) batch sorption experiments were conducted for 319 days in an inert glovebag with a variety of cementitious materials (aged cement, Vault 2, TR545, and TR547) containing varying amounts of blast furnace slag. Between 154 and 319 days, the {sup 99}Tc aqueous concentrations tended to remain constant and samples amended with different initial {sup 99}Tc concentrations, tended to merge at about 10{sup -9} M for Vault 2 (17% slag) and TR545 (90% slag) and 10{sup -8} M for TR547 (45% slag). This data provided strong evidence that solubility, and not adsorption (K{sub d} values), was controlling aqueous {sup 99}Tc concentrations. Laboratory data superimposed over thermodynamic speciation diagrams further supported the conclusion that solubility, and not adsorption controlled {sup 99}Tc aqueous concentrations. The oxidation state of the aqueous {sup 99}Tc at the end of the sorption experiment was determined by solvent extraction to be almost entirely {sup 99}Tc(VII). The pH of the present system was ~11.8. Previously proposed solubility controlling phases including Tc-sulfides may be present, but do not appear to control solubility. After the 319 day sorption period, the suspensions were removed from the glovebag and a desorption step under oxic conditions was conducted for 20 days by adding oxic, pH-buffered solutions to the suspensions. {sup 99}Tc aqueous concentrations increased by more than an order of magnitude and Eh increased by several hundred millivolts within 24 hours after the introduction of the oxic solutions. These desorption results are consistent with re-oxidation and dissolution/desorption of {sup 99}Tc(IV) phases possibly present in the cementitious materials after the anoxic sorption step of the experiment. Aqueous {sup 99}Tc concentrations continued to increase

Research commenced in FY 97 to determine the suitability of superplasticized cement-sand grouts for backfilling vertical boreholes used with geothermal heat pump (GHP) systems. The overall objectives were to develop, evaluate and demonstrate cementitious grouts that could reduce the required bore length and improve the performance of GHPs. This report summarizes the accomplishments in FY 98.

Disclosed are methods for determining the redox condition of cementitious materials. The methods are leaching methods that utilize an in situ redox indicator that is present in the cementitious materials as formed. The in situ redox indicator leaches from cementitious material and, when the leaching process is carried out under anaerobic conditions can be utilized to determine the redox condition of the material. The in situ redox indicator can exhibit distinct characteristics in the leachate depending upon the redox condition of the indicator.

Many multiscale solid state phenomena involve the transport of chemical species over large distances. This is true of crack growth in corrosive environments as well as diffusional phase transformations. Often these phenomena occur over time scales that are too long for a direct atomistic simulation. Instead continuum methods that draw on phenomenological kinetic parameters such as diffusion coefficients or thermodynamic response functions such as informed cohesive zone models are necessary. A link between first principles atomistic methods and macroscopic kinetic parameters or response functions can be made with statistical mechanical coarse-graining techniques. For multicomponent crystalline solids, this involves integrating out fast degrees of freedom to generate a coarse-grained first-principles lattice model Hamiltonian that is suited for calculating both thermodynamic and kinetic properties, the latter with the help of Green-Kubo methods. We illustrate this approach by describing (i) a first principles calculation of diffusion coefficients in non-dilute alloys, essential input for continuum simulations of diffusional phase transformations and (ii) a first principles derivation of a cohesive zone model in the presence of highly mobile impurities. Cohesive zone models are used to describe the response of a solid ahead of the crack tip in continuum simulations of crack growth. We will show that for some systems, stress induced phase transformations can occur along the cohesive zone above a critical impurity chemical potential. The stress-induced transformation is accompanied by a saturation of the cohesive zone region with impurities and leads to a dramatic reduction of critical stress for decohesion.

Engineered cementitious composites (ECC) are ultra-ductile fiber-reinforced cementitious composites. The nanoscale chemical and mechanical properties of three ECC formulae (one standard formula, and two containing nanomaterial additives) were studied using nanoindentation, electron microscopy, and energy dispersive spectroscopy. Nanoindentation results highlight the difference in modulus between bulk matrix ({approx} 30 GPa) and matrix/fiber interfacial transition zones as well as between matrix and unreacted fly ash ({approx} 20 GPa). The addition of carbon black or carbon nanotubes produced little variation in moduli when compared to standard M45-ECC. The indents were observed by electron microscopy; no trace of the carbon black particles could be found, but nanotubes, including nanotubes bridging cracks, were easily located in ultrafine cracks near PVA fibers. Elemental analysis failed to show a correlation between modulus and chemical composition, implying that factors such as porosity have more of an effect on mechanical properties than elemental composition.

The MultiScale ThermoHydrologic Model (MSTHM) is used in the total system performance assessment (TSPA) for the proposed nuclear-waste repository at Yucca Mountain. The MSTHM uses the Nonisothermal Unsaturated Flow and Transport (NUFT) code to represent thermal-hydrologic (TH) processes occurring at scales from a few tens of centimeters around individual waste packages and emplacement drifts (tunnels) all the way to the kilometer scale for heat flow through the mountain. The MSTHM is used to predict the anticipated range of TH conditions within emplacement drifts and adjoining host rock. To be defensible, the range in predicted TH conditions must address the influence of the variability and uncertainty of engineered- and natural-system parameters that significantly influence those conditions. Parameter-sensitivity analyses show that the most important natural-system parameters are host-rock thermal conductivity and percolation flux through the repository. These analyses show that the key engineered-system parameter is the waste-package-to-waste- package variability in heat output. The range in TH conditions is also influenced by the "edge-cooling" effect, where waste packages closer to the repository edge cool more quickly than those closer to the repository center. To account for this effect, the MSTHM represents the geometric details of the repository layout. Improvements have also been made to how the MSTHM incorporates hydrostratigraphic and percolation-flux data from the Unsaturated Zone Flow Model, which supports ambient flow and transport simulations for TSPA. Other improvements allow more parameter sensitivity cases to be investigated. Twelve cases are analyzed, including four percolation-flux scenarios (10-, 30-, 50- and 90-percentile) and three host-rock thermal-conductivities (10- percentile, mean, and 90-percentile). Using the results of stochastic analyses, weighting factors are applied to the twelve cases. This work was performed under the auspices of

Measured distribution coefficients (K{sub d} values) for environmental contaminants provide input data for performance assessments (PA) that evaluate physical and chemical phenomena for release of radionuclides from wasteforms, degradation of engineered components and subsequent transport of radionuclides through environmental media. Research efforts at SRNL to study the effects of formulation and curing variability on the physiochemical properties of the saltstone wasteform produced at the Saltstone Disposal Facility (SDF) are ongoing and provide information for the PA and Saltstone Operations. Furthermore, the range and distribution of plutonium K{sub d} values in soils is not known. Knowledge of these parameters is needed to provide guidance for stochastic modeling in the PA. Under the current SRS liquid waste processing system, supernate from F & H Tank Farm tanks is processed to remove actinides and fission products, resulting in a low-curie Decontaminated Salt Solution (DSS). At the Saltstone Production Facility (SPF), DSS is mixed with premix, comprised of blast furnace slag (BFS), Class F fly ash (FA), and portland cement (OPC) to form a grout mixture. The fresh grout is subsequently placed in SDF vaults where it cures through hydration reactions to produce saltstone, a hardened monolithic waste form. Variation in saltstone composition and cure conditions of grout can affect the saltstone's physiochemical properties. Variations in properties may originate from variables in DSS, premix, and water to premix ratio, grout mixing, placing, and curing conditions including time and temperature (Harbour et al. 2007; Harbour et al. 2009). There are no previous studies reported in the literature regarding the range and distribution of K{sub d} values in cementitious materials. Presently, the Savannah River Site (SRS) estimate ranges and distributions of K{sub d} values based on measurements of K{sub d} values made in sandy SRS sediments (Kaplan 2010). The actual

Calcium–silicate–hydrate (C–S–H) gel, the main product of cement hydration, contributes the most to engineering properties of concrete. Hence, the microstructural physical and mechanical properties of C–S–H gel present in cementitious composites were investigated by the coupled nanoindentation and scanning electron microscope analysis. The physical and mechanical properties were linked through the micro-poromechanical approach. Through this study, an insight was provided into the microstructural features of C–S–H gel present in cementitious composites. It is found that C–S–H gel is a multi-scale composite composed of C–S–H solid, pore and intermixtures at the scale of nanoindentation on C–S–H gel, and the physical and mechanical properties of C–S–H gel can be influenced by the porosity and volume fraction of the intermixtures. - Highlights: • A coupled nanoindentation and scanning electron microscope technique was applied. • The physical and mechanical properties were linked by the proposed model. • The porosity and poroelastic parameters were reported for the first time. • The influence of water to cement ratio was studied.

The Magnetospheric Multiscale (MMS) mission is a Solar-Terrestrial Probe mission consisting of four identically instrumented spin-stabilized spacecraft flying in an adjustable pyramid-like formation around the Earth. The formation of the MMS spacecraft allows for three-dimensional study of the phenomenon of magnetic reconnection, which is the primary objective of the mission. The MMS spacecraft were launched early on March 13, 2015 GMT. Due to the challenging and very constricted attitude and orbit requirements for performing the science, as well as the need to maintain the spacecraft formation, multiple ground functionalities were designed to support the mission. These functionalities were incorporated into a ground system known as the Attitude Ground System (AGS). Various AGS configurations have been used widely to support a variety of three-axis-stabilized and spin-stabilized spacecraft missions within the NASA Goddard Space Flight Center (GSFC). The original MMS operational concept required the AGS to perform highly accurate predictions of the effects of environmental disturbances on the spacecraft orientation and to plan the attitude maneuvers necessary to stay within the science attitude tolerance. The orbit adjustment requirements for formation control drove the need also to perform calibrations that have never been done before in support of NASA GSFC missions. The MMS mission required support analysts to provide fast and accurately calibrated values of the inertia tensor, center of mass, and accelerometer bias for each MMS spacecraft. During early design of the AGS functionalities, a Kalman filter for estimating the attitude, body rates, center of mass, and accelerometer bias, using only star tracker and accelerometer measurements, was heavily analyzed. A set of six distinct filters was evaluated and considered for estimating the spacecraft attitude and body rates using star tracker data only. Four of the six filters are closely related and were compared

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Spatial pattern formation in stiff thin films on soft substrates is investigated from a multi-scale point of view based on a technique of slowly varying Fourier coefficients. A general macroscopic modeling framework is developed and then a simplified macroscopic model is derived. The model incorporates Asymptotic Numerical Method (ANM) as a robust path-following technique to trace the post-buckling evolution path and to predict secondary bifurcations. The proposed multi-scale finite element framework allows sinusoidal and square checkerboard patterns as well as their bifurcation portraits to be described from a quantitative standpoint. Moreover, it provides an efficient way to compute large-scale instability problems with a significant reduction of computational cost compared to full models.

Cardiovascular diseases (CVDs) have been regarding as "the world's first killer" of human beings in recent years owing to the striking morbidity and mortality, the involved molecular mechanisms are extremely complex and remain unclear. Traditional Chinese medicine (TCM) adheres to the aim of combating complex diseases from an integrative and holistic point of view, which has shown effectiveness in CVDs therapy. However, system-level understanding of such a mechanism of multi-scale treatment strategy for CVDs is still difficult. Here, we developed a system pharmacology approach with the purpose of revealing the underlying molecular mechanisms exemplified by a famous compound saffron formula (CSF) in treating CVDs. First, by systems ADME analysis combined with drug targeting process, 103 potential active components and their corresponding 219 direct targets were retrieved and some key interactions were further experimentally validated. Based on this, the network relationships among active components, targets and diseases were further built to uncover the pharmacological actions of the drug. Finally, a "CVDs pathway" consisted of several regulatory modules was incorporated to dissect the therapeutic effects of CSF in different pathological features-relevant biological processes. All this demonstrates CSF has multi-scale curative activity in regulating CVD-related biological processes, which provides a new potential way for modern medicine in the treatment of complex diseases. PMID:26813334

Cardiovascular diseases (CVDs) have been regarding as “the world’s first killer” of human beings in recent years owing to the striking morbidity and mortality, the involved molecular mechanisms are extremely complex and remain unclear. Traditional Chinese medicine (TCM) adheres to the aim of combating complex diseases from an integrative and holistic point of view, which has shown effectiveness in CVDs therapy. However, system-level understanding of such a mechanism of multi-scale treatment strategy for CVDs is still difficult. Here, we developed a system pharmacology approach with the purpose of revealing the underlying molecular mechanisms exemplified by a famous compound saffron formula (CSF) in treating CVDs. First, by systems ADME analysis combined with drug targeting process, 103 potential active components and their corresponding 219 direct targets were retrieved and some key interactions were further experimentally validated. Based on this, the network relationships among active components, targets and diseases were further built to uncover the pharmacological actions of the drug. Finally, a “CVDs pathway” consisted of several regulatory modules was incorporated to dissect the therapeutic effects of CSF in different pathological features-relevant biological processes. All this demonstrates CSF has multi-scale curative activity in regulating CVD-related biological processes, which provides a new potential way for modern medicine in the treatment of complex diseases. PMID:26813334

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the United States Department of Energy (US DOE) Office of Waste Processing. The objective of the CBP project is to develop a set of tools to improve understanding and prediction of the long-term structural, hydraulic, and chemical performance of cementitious barriers used in nuclear applications.

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the United States Department of Energy (US DOE) Office of Waste Processing. The objective of the CBP project is to develop a set of tools to improve understanding and prediction of the long-term structural, hydraulic, and chemical performance of cementitious barriers used in nuclear applications.

Non-cementitious compositions and products are provided. The compositions of the invention include a carbonate additive comprising vaterite such as reactive vaterite. Additional aspects of the invention include methods of making and using the non-cementitious compositions and products.

Ubiquitous non-Gaussianity of the probability density of (time-series) fluctuations in many real world phenomena has been known and modelled extensively in recent years. Similarly, the analysis of (multi)scaling properties of (fluctuations in) complex systems has become a standard way of addressing unknown complexity. Yet the combined analysis and modelling of multiscale behaviour of probability density — multiscale PDF analysis — has only recently been proposed for the analysis of time series arising in complex systems, such as the cardiac neuro-regulatory system, financial markets or hydrodynamic turbulence. This relatively new technique has helped significantly to expand the previously obtained insights into the phenomena addressed. In particular, it has helped to identify a novel class of scale invariant behaviour of the multiscale PDF in healthy heart rate regulation during daily activity and in a market system undergoing crash dynamics. This kind of invariance reflects invariance of the system under renormalisation and resembles behaviour at criticality of a system undergoing continuous phase transition — indeed in both phenomena, such phase transition behaviour has been revealed. While the precise mechanism underlying invariance of the PDF under system renormalisation of both systems discussed is not to date understood, there is an intimate link between the non-Gaussian PDF characteristics and the persistent invariant correlation structure emerging between fluctuations across scale and time.

The motivation of this work is based on development of new construction products with strain hardening cementitious composites (SHCC) geared towards sustainable residential applications. The proposed research has three main objectives: automation of existing manufacturing systems for SHCC laminates; multi-level characterization of mechanical properties of fiber, matrix, interface and composites phases using servo-hydraulic and digital image correlation techniques. Structural behavior of these systems were predicted using ductility based design procedures using classical laminate theory and structural mechanics. SHCC sections are made up of thin sections of matrix with Portland cement based binder and fine aggregates impregnating continuous one-dimensional fibers in individual or bundle form or two/three dimensional woven, bonded or knitted textiles. Traditional fiber reinforced concrete (FRC) use random dispersed chopped fibers in the matrix at a low volume fractions, typically 1-2% to avoid to avoid fiber agglomeration and balling. In conventional FRC, fracture localization occurs immediately after the first crack, resulting in only minor improvement in toughness and tensile strength. However in SHCC systems, distribution of cracking throughout the specimen is facilitated by the fiber bridging mechanism. Influence of material properties of yarn, composition, geometry and weave patterns of textile in the behavior of laminated SHCC skin composites were investigated. Contribution of the cementitious matrix in the early age and long-term performance of laminated composites was studied with supplementary cementitious materials such as fly ash, silica fume, and wollastonite. A closed form model with classical laminate theory and ply discount method, coupled with a damage evolution model was utilized to simulate the non-linear tensile response of these composite materials. A constitutive material model developed earlier in the group was utilized to characterize and

This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

Purpose Several established optical imaging approaches have been applied, usually in isolation, to preclinical studies; however, truly useful in vivo imaging may require a simultaneous combination of imaging modalities to examine dynamic characteristics of cells and tissues. We developed a new multimode optical imaging system designed to be application-versatile, yielding high sensitivity, and specificity molecular imaging. Procedures We integrated several optical imaging technologies, including fluorescence intensity, spectral, lifetime, intravital confocal, two-photon excitation, and bioluminescence, into a single system that enables functional multiscale imaging in animal models. Results The approach offers a comprehensive imaging platform for kinetic, quantitative, and environmental analysis of highly relevant information, with micro-to-macroscopic resolution. Applied to small animals in vivo, this provides superior monitoring of processes of interest, represented here by chemo-/nanoconstruct therapy assessment. Conclusions This new system is versatile and can be optimized for various applications, of which cancer detection and targeted treatment are emphasized here. PMID:21874388

Land system changes are central to the food security challenge. Land system science can contribute to sustainable solutions by an integrated analysis of land availability and the assessment of the tradeoffs associated with agricultural expansion and land use intensification. A land system perspective requires local studies of production systems to be contextualised in a regional and global context, while global assessments should be confronted with local realities. Understanding of land governance structures will help to support the development of land use policies and tenure systems that assist in designing more sustainable ways of intensification. Novel land systems should be designed that are adapted to the local context and framed within the global socio-ecological system. Such land systems should explicitly account for the role of land governance as a primary driver of land system change and food production. PMID:24143158

In this paper, we introduce a multiscale stochastic simulation algorithm (MSSA) which makes use of Gillespie's stochastic simulation algorithm (SSA) together with a new stochastic formulation of the partial equilibrium assumption (PEA). This method is much more efficient than SSA alone. It works even with a very small population of fast species. Implementation details are discussed, and an application to the modeling of the heat shock response of E. Coli is presented which demonstrates the excellent efficiency and accuracy obtained with the new method.

The Multiscale Epidemiologic/Economic Simulation and Analysis (MESA) Decision Support System (DSS) is the product of investments that began in FY05 by the Department of Homeland Security (DHS) Science and Technology Directorate and continue today with joint funding by both DHS and the US Department of Agriculture (USDA). The DSS consists of a coupled epidemiologic/economic model, a standalone graphical user interface (GUI) that supports both model setup and post-analysis, and a Scenario Bank archive to store all content related to foreign animal disease (FAD) studies. The MESA epi model is an object-oriented, agent-based, stochastic, spatio-temporal simulator that parametrically models FAD outbreaks and response strategies from initial disease introduction to conclusion over local, regional, and national scales. Through its output database, the epi model couples to an economic model that calculates farm-level impacts from animal infections, responsive control strategies and loss of trade. The MESA architecture contains a variety of internal models that implement the major components of the epi simulation, including disease introduction, intra-herd spread, inter-herd spread (direct and indirect), detection, and various control strategies (movement restrictions, culling, vaccination) in a highly configurable and extensible fashion. MESA development was originally focused to support investigations into the economic and agricultural industry impacts associated with Foot-and-Mouth Disease (FMD outbreaks). However, it has been adapted to other FADs such has Highly Pathogenic Avian Influenza (HPAI), Classical Swine Fever (CSF) and Exotic Newcastle Disease (END). The MESA model is highly parameterized and employs an extensible architecture that permits straightforward addition of new component models (e.g., alternative disease spread approaches) when necessary. Since its inception, MESA has been developed with a requirement to enable simulation of the very large scale

The unified Non-hydrostatic Multi-scale Model on the Arakawa B grid (NMMB) is being developed at NCEP within the National Environmental Modeling System (NEMS). The finite-volume horizontal differencing employed in the model preserves important properties of differential operators and conserves a variety of basic and derived dynamical and quadratic quantities. Among these, conservation of energy and enstrophy improves the accuracy of nonlinear dynamics of the model. Within further model development, advection schemes of fourth order of formal accuracy have been developed. It is argued that higher order advection schemes should not be used in the thermodynamic equation in order to preserve consistency with the second order scheme used for computation of the pressure gradient force. Thus, the fourth order scheme is applied only to momentum advection. Three sophisticated second order schemes were considered for upgrade. Two of them, proposed in Janjic(1984), conserve energy and enstrophy, but with enstrophy calculated differently. One of them conserves enstrophy as computed by the most accurate second order Laplacian operating on stream function. The other scheme conserves enstrophy as computed from the B grid velocity. The third scheme (Arakawa 1972) is arithmetic mean of the former two. It does not conserve enstrophy strictly, but it conserves other quadratic quantities that control the nonlinear energy cascade. Linearization of all three schemes leads to the same second order linear advection scheme. The second order term of the truncation error of the linear advection scheme has a special form so that it can be eliminated by simply preconditioning the advected quantity. Tests with linear advection of a cone confirm the advantage of the fourth order scheme. However, if a localized, large amplitude and high wave-number pattern is present in initial conditions, the clear advantage of the fourth order scheme disappears. In real data runs, problems with noisy data may

Nuclear waste repositories need highly durable cementitious materials to function for over thousands of years while resisting leaching and degradation. The durability of cementitious material can be effectively improved by reducing permeability and by changing cement hydrates to a less soluble matrix. This paper describes the properties of carbonated new cementitious materials containing belite-rich cement and {gamma}-2CaO . SiO{sub 2} as main components. In addition, the long-term leaching properties are investigated and compared with ordinary Portland cement by using a predictive leaching model.

A cooperative research and development effort has been conducted to design and implement a plume-in-grid (PinG) modeling techniques into the Models-3 Community Multiscale Air Quality (CMAQ) modeling system in order to address the need for an improved modeling approach to treat major point source emissions. Objectives are to provide an improved characterization of the near-source concentration field and a better far-field regional pollutant pattern due to the impact of the plume-in-grid approach. The conceptual design and an overview of the science processes contained in the PDM in PinG algorithms are briefly presented. Test simulations with and without the PinG treatment for a major NO{sub x} point source are described, and an O{sub 3} concentration pattern from the grid model reveals the impact of the plume-in-grid approach. Subgrid scale plume cell O{sub 3} concentrations are also shown.

The concept of energy exchange between coupled oscillators can be endowed for wide variety of applications such as control and energy harvesting. It has been proved that by coupling an essential nonlinear oscillator (cubic nonlinearity) to a main system (mostly linear), the latter system can be controlled in a one way and almost irreversible manner. The phenomenon is called energy pumping and the coupled nonlinear system is named as nonlinear energy sink (NES). The process of energy transfer from the main system to the nonlinear smooth or non-smooth attachment at different scales of time can present several scenarios: It can be attracted to periodic behaviors which present low or high energy levels for the main system and/or to quasi-periodic responses of two oscillators by persistent bifurcations between their stable zones. In this paper we analyze multi-scale dynamics of two attached oscillators: a Bouc-Wen type in general (in particular: a Dahl type and a modified hysteresis system) and a NES (nonsmooth and cubic). The system behavior at fast and first slow times scales by detecting its invariant manifold, its fixed points and singularities will be analyzed. Analytical developments will be accompanied by some numerical examples for systems that present quasi-periodic responses. The endowed Bouc-Wen models correspond to the hysteretic behavior of materials or structures. This paper is clearly connected with the dynamics of systems with hysteresis and nonlinear dynamics based energy harvesting.

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

This paper documents the transport of gaseous species through porous media, with application to cementitious materials. An artificial pore network was created based on mercury intrusion porometry results obtained with samples of cement paste. The flow architecture model consists of parallel channels made of assemblies of truncated cones. Gas diffusion is described as a function of the saturation degree of the material. The model accounts for the effects of the liquid curtains, and the impact of tortuosity on gas diffusion. The results show that constructing an artificial architecture based on Hg porometry allows us to describe with a good accuracy the material porous network. The liquid curtains operate as an obstacle to H2 diffusion. They are determined as a function of the water saturation level and the pore channels geometry. Furthermore, the role of tortuosity as an indicator of gas diffusion accessibility is captured. The sudden drop in the effective diffusion coefficient around a saturation degree of 70% is predicted accurately.

This paper describes analytical methods that can be used to determine the deflections and stresses in highly compliant graphite-reinforced cementitious composites. It is demonstrated that the standard transform section fails to provide accurate results when the elastic modulus ratio exceeds 20. So an alternate approach is formulated by using the rule of mixtures to determine a set of effective material properties for the composite. Tensile tests are conducted on composite samples to verify this approach; and, when the effective material properties are used to characterize the deflections of composite beams subject to pure bending, an excellent agreement is obtained. Laminated composite plate theory is also investigated as a means for analyzing even more complex composites, consisting of multiple graphite layers oriented in different directions. In this case, composite beams are analyzed by incorporating material properties established from tensile tests. Finite element modeling is used to verity the results and, considering the complexity of the samples, a very good agreement is obtained.

Cementitious materials are increasingly used as engineered barriers and waste forms for radiological waste disposal. Yet their potential effect on mobile colloid generation is not well-known, especially as it may influence colloid-facilitated contaminant transport. Whereas previous papers have studied the introduction of cement colloids into sediments, this study examined the influence of cement leachate chemistry on the mobilization of colloids from a subsurface sediment collected from the Savannah River Site, USA. A sharp mobile colloid plume formed with the introduction of a cement leachate simulant. Colloid concentrations decreased to background concentrations even though the aqueous chemical conditions (pH and ionic strength) remained unchanged. Mobile colloids were mainly goethite and to a lesser extent kaolinite. The released colloids had negative surface charges and the mean particle sizes ranged primarily from 200 to 470 nm. Inherent mineralogical electrostatic forces appeared to be the controlling colloid removal mechanism in this system. In the background pH of ~6.0, goethite had a positive surface charge, whereas quartz (the dominant mineral in the immobile sediment) and kaolinite had negative surface charges. Goethite acted as a cementing agent, holding kaolinite and itself onto the quartz surfaces due to the electrostatic attraction. Once the pH of the system was elevated, as in the cementitious high pH plume front, the goethite reversed to a negative charge, along with quartz and kaolinite, then goethite and kaolinite colloids were mobilized and a sharp spike in turbidity was observed. Simulating conditions away from the cementitious source, essentially no colloids were mobilized at 1:1000 dilution of the cement leachate or when the leachate pH was ≤ 8. Extreme alkaline pH environments of cementitious leachate may change mineral surface charges, temporarily promoting the formation of mobile colloids. PMID:22316126

On the basis of a comprehensive data set of precisely determined depths of 121 large to moderate-sized earthquakes along and near the entire East African Rift System (EARS), there are three distinct patterns in focal depths which seem to correlate with progressive stages in the development of the largest active rift in the world. First, away from both ends of the western, younger branch of the EARS, very large (Mw ≥ 7) earthquakes occurred in the top 15 km of the crust where surficial expressions of rifting are yet to appear. Curiously, there are unusually deep aftershocks reaching down to 35 ± 3 km. Second, under well-developed but amagmatic rift segments, focal depths show a bimodal distribution, with peaks centered near depths of about 15 ± 5 km and 35 ± 5 km. This pattern is present both under the main axis of the EARS, where rift zone have lengths approaching 1000 km, and beneath rift units 10 times shorter in length. Underside reflections off the Moho indicate that at least part of the second peak in seismicity is due to mantle earthquakes down to 44 ± 4 km, attesting to high differential stress in the mantle lithosphere which is capable of accumulating seismogenic, elastic strain (the "jelly sandwich" rheology). Third, beneath magmatic segments of well-developed rifts, seismicity is largely confined to the upper 15 km of the crust as observed previously, akin to the pattern along mid-ocean ridges where plastic flow due to high temperature inhibits accumulation of shear stress deep in the lithosphere.

A high-resolution numerical model system is essential to resolve multi-scale coastal ocean dynamics. So a multi-scale unstructured grid-based finite-volume coastal ocean model (FVCOM) system has been established for the East China Sea and Changjiang Estuary (ECS-CE) with the aim at resolving coastal ocean dynamics and understanding different physical processes. The modeling system consists of a three-domain-nested weather research and forecasting model, FVCOM model with the inclusion of FVCOM surface wave model in order to understand the wave-current interactions. The ECS-CE system contains three different scale models: a shelf-scale model for the East China Sea, an estuarine-scale model for the Changjiang Estuary and adjacent region, and a fine-scale model for the deep waterway regions. These three FVCOM-based models guarantee the conservation of mass and momentum transferring from outer domain to inner domain using the one-way common-grid nesting procedure. The model system has been validated using data from various observation data, including surface wind, tides, currents, salinity, and wave to accurately reveal the multi-scale dynamics of the East China Sea and Changjiang Estuary. This modeling system has been demonstrated via application to the seasonal variations of Changjiang diluted water and the bottom saltwater intrusion in the North Passage, and it shows strong potential for estuarine and coastal ocean dynamics and operational forecasting.

A novel experimental technique, Cure Reference Method (CRM), was developed for the measurement of surface shrinkage in cementitious materials. The technique combines the replication of diffraction grating on a specimen during the curing process and the use of high-sensitivity moire interferometry. Once demolded, the specimen was stored in an environmental chamber in order to establish specific curing conditions. Measurements were conducted on a daily basis for the duration of 7 days by recording a set of the consecutive phase shifted fringe patterns using the Portable Engineering Moire interferometer II (PEMI II). An automated fringe analysis system was developed and used to obtain displacement and strain information in two dimenzsions. Surface shrinkage behavior in both cement paste and mortar specimens was investigated by the use of the technique under controlled temperature and humidity conditions. Furthermore, an experimental control was developed in an effort to remove the effects of drying shrinkage on cementitious specimens at early ages. This was done in an effort to explore the relative contribution of autogenous shrinkage to the overall shrinkage in cementitious materials.

Calcium silicate slag is an alkali leaching waste generated during the process of extracting Al2O3 from high-alumina fly ash. In this research, a cementitious material composed of calcium silicate slag was developed, and its mechanical and physical properties, hydration characteristics and environmental friendly performance were investigated. The results show that an optimal design for the cementitious material composed of calcium silicate slag was determined by the specimen CFSC7 containing 30% calcium silicate slag, 5% high-alumina fly ash, 24% blast furnace slag, 35% clinker and 6% FGD gypsum. This blended system yields excellent physical and mechanical properties, confirming the usefulness of CFSC7. The hydration products of CFSC7 are mostly amorphous C-A-S-H gel, rod-like ettringite and hexagonal-sheet Ca(OH)2 with small amount of zeolite-like minerals such as CaAl2Si2O8·4H2O and Na2Al2Si2O8·H2O. As the predominant hydration products, rod-like ettringite and amorphous C-A-S-H gel play a positive role in promoting densification of the paste structure, resulting in strength development of CFSC7 in the early hydration process. The leaching toxicity and radioactivity tests results indicate that the developed cementitious material composed of calcium silicate slag is environmentally acceptable. This study points out a promising direction for the proper utilization of calcium silicate slag in large quantities. PMID:26691955

Electric energy storage systems such as batteries can significantly impact society in a variety of ways, including facilitating the widespread deployment of portable electronic devices, enabling the use of renewable energy generation for local off grid situations and providing the basis of highly efficient power grids integrated with energy production, large stationary batteries, and the excess capacity from electric vehicles. A critical challenge for electric energy storage is understanding the basic science associated with the gap between the usable output of energy storage systems and their theoretical energy contents. The goal of overcoming this inefficiency is to achieve more useful work (w) and minimize the generation of waste heat (q). Minimization of inefficiency can be approached at the macro level, where bulk parameters are identified and manipulated, with optimization as an ultimate goal. However, such a strategy may not provide insight toward the complexities of electric energy storage, especially the inherent heterogeneity of ion and electron flux contributing to the local resistances at numerous interfaces found at several scale lengths within a battery. Thus, the ability to predict and ultimately tune these complex systems to specific applications, both current and future, demands not just parametrization at the bulk scale but rather specific experimentation and understanding over multiple length scales within the same battery system, from the molecular scale to the mesoscale. Herein, we provide a case study examining the insights and implications from multiscale investigations of a prospective battery material, Fe3O4. PMID:27413781

Electric energy storage systems such as batteries can significantly impact society in a variety of ways, including facilitating the widespread deployment of portable electronic devices, enabling the use of renewable energy generation for local off grid situations and providing the basis of highly efficient power grids integrated with energy production, large stationary batteries, and the excess capacity from electric vehicles. A critical challenge for electric energy storage is understanding the basic science associated with the gap between the usable output of energy storage systems and their theoretical energy contents. The goal of overcoming this inefficiency is to achieve more useful work (w) and minimize the generation of waste heat (q). Minimization of inefficiency can be approached at the macro level, where bulk parameters are identified and manipulated, with optimization as an ultimate goal. However, such a strategy may not provide insight toward the complexities of electric energy storage, especially the inherent heterogeneity of ion and electron flux contributing to the local resistances at numerous interfaces found at several scale lengths within a battery. Thus, the ability to predict and ultimately tune these complex systems to specific applications, both current and future, demands not just parametrization at the bulk scale but rather specific experimentation and understanding over multiple length scales within the same battery system, from the molecular scale to the mesoscale. Herein, we provide a case study examining the insights and implications from multiscale investigations of a prospective battery material, Fe3O4. PMID:27413781

Multi scale systems offer the opportunity to balance the conflict between execution time, measurement volume and resolution for the inspection of highly complex surface profiles. An example of such a task is the inspection of gears. At first, the coarse position and form of the specimen is registered by a sensor measuring with comparatively low resolution but a large field of view. Possible defects near to the resolution limit are indicated and new regions of interest for higher resolved measurements are identified. As prerequisite for a successful multi-scale inspection, every sampled data set, acquired in different scales and at varying positions, must be registered in one global data model. This is only possible if the extrinsic coordinate transform from the sensor's internal coordinate system to the common, global coordinate system of the inspected object and its uncertainties are known. In this paper, we present an approach for the extrinsic calibration using the example of a multi-zoom fringe projection sensor mounted on a multi-axes measurement system. Finally we show the measurement result of a gear, where several sampled patches are merged together into one point cloud with the aid of the presented calibration.

A multi-scale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The GCM allows global coverage and the CRM allows explicit simulation of cloud processes and their interactions with radiation and surface processes. A new MMF has been developed that is based the Goddard finite volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved .surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger, propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using conventional cloud parameterizations. Both MMFs also produce a precipitation bias in the western Pacific during Northern Hemisphere summer. However, there are also notable differences between two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF overestimates global rainfall because of its oceanic component. Some critical issues associated with the Goddard MMF are presented in this paper.

Fragmentation of grasslands has been implicated in grassland bird population declines. Multi-scale models are being increasingly used to assess potential factors that influence grassland bird presence, abundance, and productivity. However, studies rarely assess fragmentation metrics, and seldom evaluate more than two scales or interactions among scales. We evaluated the relative importance of characteristics at multiple scales to patterns in relative abundance of Savannah Sparrow (Passerculus sandwichensis), Grasshopper Sparrow (Ammodramus savannarum), Eastern Meadowlark (Sturnella magna), and Bobolink (Dolichonyx oryzivorus). We surveyed birds in 74 southwestern Wisconsin pastures from 1997 to 1999 and compared models with explanatory variables from multiple scales: within-patch vegetation structure (microhabitat), patch (macrohabitat), and three landscape extents. We also examined interactions between macrohabitat and landscape factors. Core area of pastures was an important predictor of relative abundance, and composition of the landscape was more important than configuration. Relative abundance was frequently higher in pastures with more core area and in landscapes with more grassland and less wooded area. The direction and strength of the effect of core pasture size on relative abundance changed depending on amount of wooded area in the landscape. Relative abundance of grassland birds was associated with landscape variables more frequently at the 1200-m scale than at smaller scales. To develop better predictive models, parameters at multiple scales and their interactive effects should be included, and results should be evaluated in the context of microhabitat variability, landscape composition, and fragmentation in the study area. ?? 2007 Springer Science+Business Media B.V.

Background Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. Methods Twenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients. Results Statistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify

One of the fundamental characteristics of the brain is its hierarchical organization. Scales in both space and time that must be considered when integrating across hierarchies of the nervous system are sufficiently great as to have impeded the development of routine multilevel modeling methodologies. Complex molecular interactions at the level of receptors and channels regulate activity at the level of neurons; interactions between multiple populations of neurons ultimately give rise to complex neural systems function and behavior. This spatial complexity takes place in the context of a composite temporal integration of multiple, different events unfolding at the millisecond, second, minute, hour, and longer time scales. In this study, we present a multiscale modeling methodology that integrates synaptic models into single neuron, and multineuron, network models. We have applied this approach to the specific problem of how changes at the level of kinetic parameters of a receptor-channel model are translated into changes in the temporal firing pattern of a single neuron, and ultimately, changes in the spatiotemporal activity of a network of neurons. These results demonstrate how this powerful methodology can be applied to understand the effects of a given local process within multiple hierarchical levels of the nervous system. PMID:21642035

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

This paper presents a model for the carbonation of cementitious matrixes (UR-CORE). The model is based on the principles of the 'unreacted-core' systems, typical of chemical engineering processes, in which the reacted product remains in the solid as a layer of inert ash, adapted for the specific case of carbonation. Development of the model has been undertaken in three steps: 1) Establishment of the controlling step in the global carbonation rate, by using data of fractional conversion of different phases of the cementitious matrixes, obtained by the authors through neutron diffraction data experiments, and reported in [M. Castellote, C. Andrade, X. Turrillas, J. Campo, G. Cuello, Accelerated carbonation of cement pastes in situ monitored by neutron diffraction, Cem. Concr. Res. (2008), doi:10.1016/j.cemconres.2008.07.002]. 2) Then, the model has been adapted and applied to the cementitious materials using different concentrations of CO{sub 2}, with the introduction of the needed assumptions and factors. 3) Finally, the model has been validated with laboratory data at different concentrations (taken from literature) and for long term natural exposure of concretes. As a result, the model seems to be reliable enough to be applied to cementitious materials, being able to extrapolate the results from accelerated tests in any conditions to predict the rate of carbonation in natural exposure, being restricted, at present stage, to conditions with a constant relative humidity.

We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example of a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.

NASA's Magnetospheric Multi-Scale (MMS) mission successfully launched on March 13, 2015 (UTC) consists of four identically instrumented spin-stabilized observatories that function as a constellation to study magnetic reconnection in space. The need to maintain sufficiently accurate spatial and temporal formation resolution of the observatories must be balanced against the logistical constraints of executing overly-frequent maneuvers on a small fleet of spacecraft. These two considerations make for an extremely challenging maneuver design problem. This paper focuses on the design elements of a 6-DOF spacecraft attitude control and maneuvering system capable of delivering the high-precision adjustments required by the constellation designers---specifically, the design, implementation, and on-orbit performance of the closed-loop formation-class maneuvers that include initialization, maintenance, and re-sizing. The maneuvering control system flown on MMS utilizes a micro-gravity resolution accelerometer sampled at a high rate in order to achieve closed-loop velocity tracking of an inertial target with arc-minute directional and millimeter-per-second magnitude accuracy. This paper summarizes the techniques used for correcting bias drift, sensor-head offsets, and centripetal aliasing in the acceleration measurements. It also discusses the on-board pre-maneuver calibration and compensation algorithms as well as the implementation of the post-maneuver attitude adjustments.

Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scalesystem functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical

Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scalesystem functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the Office of Tank Waste Management within the Office of Environmental Management of U.S. Department of Energy (US DOE). The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that improve understanding and predictions of the long-term hydraulic and chemical performance of cementitious barriers used in nuclear applications. Tools selected for and developed under this program are intended to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to or longer than 100 years for operating facilities and longer than 1,000 years for waste management purposes. CBP software tools were made available to selected DOE Office of Environmental Management and field site users for training and evaluation based on a set of important degradation scenarios, including sulfate ingress/attack and carbonation of cementitious materials. The tools were presented at two-day training workshops held at U.S. National Institute of Standards and Technology (NIST), Savannah River, and Hanford included LeachXS{sup TM}/ORCHESTRA, STADIUM{sup R}, and a CBP-developed GoldSim Dashboard interface. Collectively, these components form the CBP Software Toolbox. The new U.S. Environmental Protection Agency leaching test methods based on the Leaching Environmental Assessment Framework (LEAF) were also presented. The CBP Dashboard uses a custom Dynamic-link library developed by CBP to couple to the LeachXS{sup TM}/ORCHESTRA and STADIUM{sup R} codes to simulate reactive transport and degradation in cementitious materials for selected performance assessment scenarios. The first day of the workshop introduced participants to the software components via presentation materials, and the second day included hands-on tutorial exercises followed

A Settlement Agreement between the Department of Energy (DOE) and the State of Idaho mandates that all high-level radioactive waste (HLW) now stored at the Idaho Chemical Processing Plant (ICPP) on the Idaho National Engineering and Environmental Laboratory (INEEL) will be treated so that it is ready to be moved out of Idaho for disposal by a target date of 2035. This study investigates the nonseparations Cementitious Waste Option (CWO) as a means to achieve this goal. Under this option all liquid sodium-bearing waste (SBW) and existing HLW calcine would be recalcined with sucrose, grouted, canisterized, and interim stored as a mixed-HLW for eventual preparation and shipment off-Site for disposal. The CWO waste would be transported to a Greater Confinement Disposal Facility (GCDF) located in the southwestern desert of the US on the Nevada Test Site (NTS). All transport preparation, shipment, and disposal facility activities are beyond the scope of this study. CWO waste processing, packaging, and interim storage would occur over a 5-year period between 2013 and 2017. Waste transport and disposal would occur during the same time period.

Millions of metric tons of cementitious materials are produced, transported and used in construction each year. The ease or difficulty of handling cementitious materials is greatly influenced by the material friction properties. In the present study, the coefficients of friction of cementitious materials were measured at the microscale and macroscale. The materials tested were commercially-available Portland cement, Class C fly ash, and ground granulated blast furnace slag. At the microscale, the coefficient of friction was determined from the interaction forces between cementitious particles using an Atomic Force Microscope. At the macroscale, the coefficient of friction was determined from stresses on bulk cementitious materials under direct shear. The study indicated that the microscale coefficient of friction ranged from 0.020 to 0.059, and the macroscale coefficient of friction ranged from 0.56 to 0.75. The fly ash studied had the highest microscale coefficient of friction and the lowest macroscale coefficient of friction. -- Highlights: •Microscale (interparticle) coefficient of friction (COF) was determined with AFM. •Macroscale (bulk) COF was measured under direct shear. •Fly ash had the highest microscale COF and the lowest macroscale COF. •Portland cement against GGBFS had the lowest microscale COF. •Portland cement against Portland cement had the highest macroscale COF.

Chalcogenide glasses exhibit unique properties applicable to a wide range of fields, including electrical and optical switching and the transmission of infrared radiation. In this thesis, we adopt a hierarchical multiscale modeling approach to investigate the fundamental physics of chalcogenide systems. Our multiscale modeling begins in Part I at the quantum mechanical level, where we use the highly accurate Moller-Plesset perturbation technique to derive interaction potentials for elemental and heterogeneous chalcogenide systems. The resulting potentials consist of two-, three-, and effective four-body terms. In Part II, we use these ab initio potentials in classical Monte Carlo simulations to investigate the structure of chalcogenide glasses. We discuss our simulation results in relation to the Phillips model of topological constraints, which predicts critical behavior in chalcogenide systems as a function of average coordination number. Finally, in Part III we address the issue of glass transition range behavior. After reviewing previous models of the glass transition, we derive a new model based on nonequilibrium statistical mechanics and an energy landscape formalism. The new model requires as input a description of inherent structure energies and the transition energies between these structures. To address this issue, we derive an eigenvector-following technique for mapping a multidimensional potential energy landscape. This technique is then extended for application to enthalpy landscapes. Our model will enable the first-ever calculation of glass transition behavior based on only ab initio physics.

Many processes important to chemistry, materials science, and biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system. These inherently multiscale problems require computationally efficient and accurate methods to converge statistical properties. In this paper, a method is presented that uses data directly from condensed phase ab initio simulations to develop reactive molecular dynamics models that do not require predefined empirical functions. Instead, the interactions used in the reactive model are expressed as linear combinations of interpolating functions that are optimized by using a linear least-squares algorithm. One notable benefit of the procedure outlined here is the capability to minimize the number of parameters requiring nonlinear optimization. The method presented can be generally applied to multiscale problems and is demonstrated by generating reactive models for the hydrated excess proton and hydroxide ion based directly on condensed phase ab initio molecular dynamics simulations. The resulting models faithfully reproduce the water-ion structural properties and diffusion constants from the ab initio simulations. Additionally, the free energy profiles for proton transfer, which is sensitive to the structural diffusion of both ions in water, are reproduced. The high fidelity of these models to ab initio simulations will permit accurate modeling of general chemical reactions in condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus facilitating a proper statistical sampling of the coupling to slow, large-scale motions of the system.

Many processes important to chemistry, materials science, and biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system. These inherently multiscale problems require computationally efficient and accurate methods to converge statistical properties. In this paper, a method is presented that uses data directly from condensed phase ab initio simulations to develop reactive molecular dynamics models that do not require predefined empirical functions. Instead, the interactions used in the reactive model are expressed as linear combinations of interpolating functions that are optimized by using a linear least-squares algorithm. One notable benefit of the procedure outlined here is the capability to minimize the number of parameters requiring nonlinear optimization. The method presented can be generally applied to multiscale problems and is demonstrated by generating reactive models for the hydrated excess proton and hydroxide ion based directly on condensed phase ab initio molecular dynamics simulations. The resulting models faithfully reproduce the water-ion structural properties and diffusion constants from the ab initio simulations. Additionally, the free energy profiles for proton transfer, which is sensitive to the structural diffusion of both ions in water, are reproduced. The high fidelity of these models to ab initio simulations will permit accurate modeling of general chemical reactions in condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus facilitating a proper statistical sampling of the coupling to slow, large-scale motions of the system. PMID:23249062

Using the planet as a study domain and collecting observations over unprecedented ranges of spatial and temporal scales, NASA's EOS (Earth Observing System) program was an agent of transformational change in Earth Sciences over the last thirty years. The remarkable space-time organization and variability of atmospheric and terrestrial moist processes that emerged from the analysis of comprehensive satellite observations provided much impetus to expand the scope of land-atmosphere interaction studies in Hydrology and Hydrometeorology. Consequently, input and output terms in the mass and energy balance equations evolved from being treated as fluxes that can be used as boundary conditions, or forcing, to being viewed as dynamic processes of a coupled system interacting at multiple scales. Measurements of states or fluxes are most useful if together they map, reveal and/or constrain the underlying physical processes and their interactions. This can only be accomplished through an integrated observing system designed to capture the coupled physics, including nonlinear feedbacks and tipping points. Here, we first review and synthesize lessons learned from hydrometeorology studies in the Southern Appalachians and in the Southern Great Plains using both ground-based and satellite observations, physical models and data-assimilation systems. We will specifically focus on mapping and understanding nonlinearity and multiscale memory of rainfall-runoff processes in mountainous regions. It will be shown that beyond technical rigor, variety, quantity and duration of measurements, the utility of observing systems is determined by their interpretive value in the context of physical models to describe the linkages among different observations. Second, we propose a framework for designing science-grade and science-minded process-oriented integrated observing and modeling platforms for hydrometeorological studies.

This project is presented in two sections. Two different multiscale models are developed in order to increase the computational speed of two well known atomistic algorithms, Molecular Dynamics (MD) and Kinetic Monte Carlo (KMC). In Section I, the MD method is introduced. Following this, a multiscale method of linking an MD simulation of heat conduction to a finite element (FE) simulation is presented. The method is simple to implement into a conventional MD code and is independent of the atomistic model employed. This bridge between the FE and MD simulations works by ensuring that energy is conserved across the FE/MD boundary. The multiscale simulation allows for the investigation of large systems which are beyond the range of MD. The method is tested extensively in the steady state and transient regimes, and is shown to agree with well with large scale MD and FE simulations. Furthermore, the method removes the artificial boundary effects due to the thermostats and hence allows exact temperatures and temperature gradients to be imposed on to an MD simulation. This allows for better study of temperature gradients on crystal defects etc.. In Section II, the KMC method is introduced. A continuum model for the KMC method is presented and compared to the standard KMC model of surface diffusion. This method replaces the many discrete back and forth atom jumps performed by a standard KMC algorithm with a single flux that can evolve in time. Elastic strain is then incorporated into both algorithms and used to simulate atom deposition upon a substrate by Molecular Beam Epitaxy. Quantum dot formation due to a mismatch in the lattice spacing between a substrate and a deposited film is readily observed in both models. Furthermore, by depositing alternating layers of substrate and deposit, self-organised quantum dot super-lattices are observed in both models..

Mathematical modelling has been used to comprehend the pathology and the assessment of different treatment techniques such as heart failure and left ventricular assist device therapy in the cardiovascular field. In this study, an in-silico model of the heart is developed to understand the effects of idiopathic dilated cardiomyopathy (IDC) as a pathological scenario, with mechanisms described at the cellular, protein and organ levels. This model includes the right and left atria and ventricles, as well as the systemic and pulmonary arteries and veins. First, a multi-scale model of the whole heart is simulated for healthy conditions. Subsequently, the model is modified at its microscopic and macroscopic spatial scale to obtain the characteristics of IDC. The extracellular calcium concentration, the binding affinity of calcium binding proteins and the maximum and minimum elastances have been identified as key parameters across all relevant scales. The modified parameters cause a change in (a) intracellular calcium concentration characterising cellular properties, such as calcium channel currents or the action potential, (b) the proteins being involved in the sliding filament mechanism and the proportion of the attached crossbridges at the protein level, as well as (c) the pressure and volume values at the organ level. This model allows to obtain insight and understanding of the effects of the treatment techniques, from a physiological and biological point of view. PMID:25147131

Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829

Ordinary Portland cement (OPC), the most used binder in construction, presents some disadvantages in terms of pollution (CO2 emissions) and visual impact. For this reason, green roofs and façades have gain considerable attention in the last decade as a way to integrate nature in cities. These systems, however, suffer from high initial and maintenance costs. An alternative strategy to obtain green facades is the direct natural colonisation of the cementitious construction materials constituting the wall, a phenomenon governed by the bioreceptivity of such material. This work aims at assessing the suitability of magnesium phosphate cement (MPC) materials to allow a rapid natural colonisation taking carbonated OPC samples as a reference material. For that, the aggregate size, the w/c ratio and the amount of cement paste of mortars made of both binders were modified. The assessment of the different bioreceptivities was conducted by means of an accelerated algal fouling test. MPC samples exhibited a faster fouling compared to OPC samples, which could be mainly attributed to the lower pH of the MPC binder. In addition to the binder, the fouling rate was governed by the roughness and the porosity of the material. MPC mortar with moderate porosity and roughness appears to be the most feasible material to be used for the development of green concrete walls. PMID:24602907

Structural health monitoring of civil infrastructure systems like concrete bridges and dams has become critical because of the aging and overloading of these CIS. Most of the available SHM methods are not in-situ and can be very expensive. The triboluminescence multifunctional cementitious composites (TMCC) have in-built crack detection mechanism that can enable bridge engineers to monitor and detect abnormal crack formation in concrete structures so that timely corrective action can be taken to prevent costly or catastrophic failures. This article reports the fabrication process and test result of the flexural characterization of the TMCC. Accelerated durability test indicated that the 0.5 ZnS:Mn/Epoxy weight fraction ITOF sensor configuration to be more desirable in terms of durability. The alkaline environment at the highest temperature investigated (45 °C) resulted in significant reduction in the mean glass transition and storage moduli of the tested ITOF thin films. Further work is ongoing to correlate the TL response of the TMCC with damage, particularly crack opening.

Phase-sensitive Optical-Time-Domain Reflectometry (OTDR) system is a typical distributed fiber-optic sensing technology to detect and locate multiple dynamic disturbances from the outside, which provides a cost-effective and highly sensitive solution especially for monitoring long or ultra-long perimeters. However, the system is liable to be interfered by laser frequency drifts and environmental noises due to its phase sensitivity. The fluctuant and time-varying backgrounds severely obscure real intrusion signals, which always cause bad detection results or high Nuisance Alarm Rates (NARs). In this paper, an effective signal separation method is proposed to extract true intrusion information from the complicated noisy backgrounds of phase-sensitive OTDR system. The sensing signal in the time-domain at each spatial point is obtained by accumulating the changing trails at different moments. Multi-scale wavelet decomposition is employed on the temporal signal to get the detailed components at different scales. By selectively recombining the scale components, it can easily extract the real intrusion signal, and separate the fluctuant frequency-drift induced phase noises, and the time-varying sound or other interferences caused by the air movements, which are respectively located at different time-frequency components. Moreover, the experimental results show that the event type could be divided and discerned from the time-frequency energy distribution at different scale. Thus nuisance and false alarms in practical applications of phase-sensitive OTDR system can be decreased significantly by this way of signal separation and extraction. This technique provides a useful solution for the intrusion detection and identification of the phase-sensitive OTDR in complicated environments, and paves the way for many important applications such as long perimeter security, oil or gas pipe safety monitoring, large-scale structure health detection and fault diagnosis and so on.

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach. PMID:21483730

We perform an analysis of cardiac data using multiscale entropy as proposed in Costa et al. [Multiscale entropy analysis of complex physiological time series, Phys. Rev. Lett. 89 (2002) 068102]. We reproduce the signatures of the multiscale entropy for the three cases of young healthy hearts, atrial fibrillation and congestive heart failure. We show that one has to be cautious how to interpret these signatures in terms of the underlying dynamics. In particular, we show that different dynamical systems can exhibit the same signatures depending on the sampling time, and that similar systems may have different signatures depending on the time scales involved. Besides the total amount of data we identify the sampling time, the correlation time and the period of possible nonlinear oscillations as important time scales which have to be involved in a detailed analysis of the signatures of multiscale entropies. We illustrate our ideas with the Lorenz equation as a simple deterministic chaotic system.

The thermal conductivity and other properties cementitious grouts have been investigated in order to determine suitability of these materials for grouting vertical boreholes used with geothermal heat pumps. The roles of mix variables such as water/cement ratio, sand/cement ratio and superplasticizer dosage were measured. In addition to thermal conductivity, the cementitious grouts were also tested for bleeding, permeability, bond to HDPE pipe, shrinkage, coefficient of thermal expansion, exotherm, durability and environmental impact. This paper summarizes the results for selected grout mixes. Relatively high thermal conductivities were obtained and this leads to reduction in predicted bore length and installation costs. Improvements in shrinkage resistance and bonding were achieved.

The thermal conductivity and other properties cementitious grouts have been investigated in order to determine suitability of these materials for grouting vertical boreholes used with geothermal heat pumps. The roles of mix variables such as water/cement ratio, sand/cement ratio and superplasticizer dosage were measured. In addition to thermal conductivity, the cementitious grouts were also tested for bleeding, permeability, bond to HDPE pipe, shrinkage, coefficient of thermal expansion, exotherm, durability and environmental impact. This paper summarizes the results for selected grout mixes. Relatively high thermal conductivities were obtained and this leads to reduction in predicted bore length and installation costs. Improvements in shrinkage resistance and bonding were achieved.

Sealing fractures in nuclear waste repositories concerns all programs investigating deep burial as a means of disposal. Because the most likely mechanism for contaminant migration is by dissolution and movement through groundwater, sealing programs are seeking low-viscosity sealants that are chemically, mineralogically, and physically compatible with the host rock. This paper presents the results of collaborative work directed by Sandia National Laboratories (SNL) and supported by Whiteshell Laboratories, operated by Atomic Energy of Canada, Ltd. The work was undertaken in support of the Waste Isolation Pilot Plant (WIPP), an underground nuclear waste repository located in a salt formation east of Carlsbad, NM. This effort addresses the technology associated with long-term isolation of nuclear waste in a natural salt medium. The work presented is part of the WIPP plugging and sealing program, specifically the development and optimization of an ultrafine cementitious grout that can be injected to lower excessive, strain-induced hydraulic conductivity in the fractured rock termed the Disturbed Rock Zone (DRZ) surrounding underground excavations. Innovative equipment and procedures employed in the laboratory produced a usable cement-based grout; 90% of the particles were smaller than 8 microns and the average particle size was 4 microns. The process involved simultaneous wet pulverization and mixing. The grout was used for a successful in situ test underground at the WIPP. Injection of grout sealed microfractures as small as 6 microns (and in one rare instance, 3 microns) and lowered the gas transmissivity of the DRZ by up to three orders of magnitude. Following the WIPP test, additional work produced an improved version of the grout containing particles 90% smaller than 5 microns and averaging 2 microns. This grout will be produced in dry form, ready for the mixer.

Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help in the control of glycemic fluctuations, which is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and, thus, a decreased complexity in this system. No study has investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13), who were matched for sex, age, and body mass index via MSE analysis using the CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 vs. control subjects 93.3 ± 1.5 mg/dl), the standard deviation (51.7 ± 4.3 vs. 11.1 ± 0.5 mg/dl), and the mean amplitude of glycemic excursions (127.0 ± 9.2 vs. 27.7 ± 1.3 mg/dl) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 vs. 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregulation is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes. PMID:24808497

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to human epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future

Acoustic emission (AE) signals were continuously recorded and their intrinsic frequency characteristics examined in order to evaluate the mechanical performance of cementitious wasteform samples with encapsulated Al waste. The primary frequency in the power spectrum and its range of intensity for the detected acoustic waves were potentially related with appearance of different micro-mechanical events caused by Al corrosion within the encapsulating cement system. In addition the process of cement matrix hardening has been shown as a source of AE signals characterized with essentially higher primary frequency (above 2 MHz) compared with those due to Al corrosion development (below 40 kHz) and cement cracking (above 100 kHz). (authors)

Chronic exposure to some well-absorbed but slowly eliminated xenobiotics can lead to their bioaccumulation in living organisms. Here, we studied the bioaccumulation and distribution of clofazimine, a riminophenazine antibiotic used to treat mycobacterial infection. Using mice as a model organism, we performed a multiscale, quantitative analysis to reveal the sites of clofazimine bioaccumulation during chronic, long-term exposure. Remarkably, between 3 and 8 weeks of dietary administration, clofazimine massively redistributed from adipose tissue to liver and spleen. During this time, clofazimine concentration in fat and serum significantly decreased, while the mass of clofazimine in spleen and liver increased by >10-fold. These changes were paralleled by the accumulation of clofazimine in the resident macrophages of the lymphatic organs, with as much as 90% of the clofazimine mass in spleen sequestered in intracellular crystal-like drug inclusions (CLDIs). The amount of clofazimine associated with CLDIs of liver and spleen macrophages disproportionately increased and ultimately accounted for a major fraction of the total clofazimine in the host. After treatment was discontinued, clofazimine was retained in spleen while its concentrations decreased in blood and other organs. Immunologically, clofazimine bioaccumulation induced a local, monocyte-specific upregulation of various chemokines and receptors. However, interleukin-1 receptor antagonist was also upregulated, and the acute-phase response pathways and oxidant capacity decreased or remained unchanged, marking a concomitant activation of an anti-inflammatory response. These experiments indicate an inducible, immune system-dependent, xenobiotic sequestration response affecting the atypical pharmacokinetics of a small molecule chemotherapeutic agent. PMID:23263006

An assessment of the potential effects of phosphate ions on cementitious materials was made through a review of the literature, contacts with concrete research personnel, and conduct of a "bench-scale" laboratory investigation. Results indicate that no harmful interactions occur between phosphate ions and cememtitious materials unless phosphates are present in form of phosphoric acid.

The response of the coastal ocean and estuaries to severe weather forcing (e.g. tropical and extra-tropical storms) and strong tsunamis vary significantly in space and time. Simulating and predicting this response require a) a fully coupled atmospheric-ocean model system that can resolve the multi-scale current-wave interaction processes; b) grid flexibility to accurately represent irregular geometric shelf-estuarine-wetland regions, c) computational efficiency that allows an adjustable time step with changes in the model spatial resolution, and d) a Web Map Service (WMS) display system. The UMASSD-WHOI research team has upgraded FVCOM using the Earth System Modeling Framework (ESMF). The new FVCOM has a mass-conservative two-way nesting feature that allows varying time steps for the time integration of different multi-scale global, basin, shelf, and estuarine/wetland processes. A parallelized version of WMS was also built into FVCOM, through which the model forecast fields can be viewed and analyzed directly using Google maps on the website. These new features have been implemented into the Northeast Coastal Ocean Forecast System (NECOFS) for the purpose of predicting coastal inundation caused by severe weather systems as they pass through the Northeast. The multi-domain nesting FVCOM system was also successfully used to simulate the Japan March 11 earthquake-induced tsunami waves, coastal inundation, and subsequent spread of Cs-137 into the Japan coastal ocean.

A prototype surface ozone concentration forecasting model system for the Eastern U.S. has been developed. The model system is consisting of a regional meteorological and a regional air quality model. It demonstrated a strong prediction dependence on its ozone boundary conditions....

A portion of the concrete pavements in the US have recently been observed to have premature joint deterioration. This damage is caused in part by the ingress of fluids, like water, salt water, or deicing salts. The ingress of these fluids can damage concrete when they freeze and expand or can react with the cementitious matrix causing damage. To determine the quality of concrete for assessing potential service life it is often necessary to measure the rate of fluid ingress, or sorptivity. Neutron imaging is a powerful method for quantifying fluid penetration since it can describe where water has penetrated, how quickly it has penetrated and the volume of water in the concrete or mortar. Neutrons are sensitive to light atoms such as hydrogen and thus clearly detect water at high spatial and temporal resolution. It can be used to detect small changes in moisture content and is ideal for monitoring wetting and drying in mortar exposed to various fluids. This study aimed at developing a method to accurately estimate moisture content in mortar. The common practice is to image the material dry as a reference before exposing to fluid and normalizing subsequent images to the reference. The volume of water can then be computed using the Beer-Lambert law. This method can be limiting because it requires exact image alignment between the reference image and all subsequent images. A model of neutron attenuation in a multi-phase cementitious composite was developed to be used in cases where a reference image is not available. The attenuation coefficients for water, un-hydrated cement, and sand were directly calculated from the neutron images. The attenuation coefficient for the hydration products was then back-calculated. The model can estimate the degree of saturation in a mortar with known mixture proportions without using a reference image for calculation. Absorption in mortars exposed to various fluids (i.e., deionized water and calcium chloride solutions) were investigated

In recent years, a new class of cementitious composite has been proposed for the design and construction of durable civil structures. Termed engineered cementitious composites (ECC), ECC utilizes a low volume fraction of short fibers (polymer, steel, carbon) within a cementitious matrix resulting in a composite that strain hardens when loaded in tension. By refining the mechanical properties of the fiber-cement interface, the material exhibits high tolerance to damage. This study explores the electrical properties of ECC materials to monitor their performance and health when employed in the construction of civil structures. In particular, the conductivity of ECC changes in proportion to strain indicating that the material is piezoresistive. In this paper, the piezoresistive properties of various ECC composites are thoroughly explored. To measure the electrical resistance of ECC structures in the field, a low-cost wireless active sensing unit is proposed. The wireless active sensing unit is capable of applying DC and AC voltage signals to ECC elements while simultaneously measuring their corresponding voltages away from the signal input. By locally processing the corresponding input-output electrical signals recorded by the wireless active sensing units, the magnitude of strain in ECC elements can be calculated. In addition to measuring strain, the study seeks to correlate changes in ECC electrical properties to the magnitude of crack damage witnessed in tested specimens. A large number of ECC specimens are tested in the laboratory including a large-scale ECC bridge pier laterally loaded under cyclically repeated drift reversals. The novel self-sensing properties of ECC exploited by a wireless monitoring system hold tremendous promise for the advancement of structural health monitoring of ECC structures.

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the U.S. Department of Energy (US DOE) Office of Tank Waste Management. The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that help improve understanding and predictions of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The CBP Software Toolbox – “Version 1.0” was released early in FY2013 and was used to support DOE-EM performance assessments in evaluating various degradation mechanisms that included sulfate attack, carbonation and constituent leaching. The sulfate attack analysis predicted the extent and damage that sulfate ingress will have on concrete vaults over extended time (i.e., > 1000 years) and the carbonation analysis provided concrete degradation predictions from rebar corrosion. The new release “Version 2.0” includes upgraded carbonation software and a new software module to evaluate degradation due to chloride attack. Also included in the newer version are a dual regime module allowing evaluation of contaminant release in two regimes – both fractured and un-fractured. The integrated software package has also been upgraded with new plotting capabilities and many other features that increase the “user-friendliness” of the package. Experimental work has been generated to provide data to calibrate the models to improve the credibility of the analysis and reduce the uncertainty. Tools selected for and developed under this program have been used to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to or longer than 100 years for operating facilities and longer than 1000 years for waste disposal. The CBP Software Toolbox is and will continue to produce tangible benefits to the working DOE

This paper describes a master-slave visual surveillance system that uses stationary-dynamic camera assemblies to achieve wide field of view and selective focus of interest. In this system, the fish-eye panoramic camera is capable of monitoring a large area, and the PTZ dome camera has high mobility and zoom ability. In order to achieve the precise interaction, preprocessing spatial calibration between these two cameras is required. This paper introduces a novel calibration approach to automatically calculate a transformation matrix model between two coordinate systems by matching feature points. In addition, a distortion correction method based on Midpoint Circle Algorithm is proposed to handle obvious horizontal distortion in the captured panoramic image. Experimental results using realistic scenes have demonstrated the efficiency and applicability of the system with real-time surveillance. PMID:24729750

The interest in retrofit/rehabilitation of existing concrete structures has increased due to degradation and/or introduction of more stringent design requirements. Among the externally-bonded strengthening systems fiber-reinforced polymers is the most widely known technology. Despite its effectiveness as a material system, the presence of an organic binder has some drawbacks that could be addressed by using in its place a cementitious binder as in fabric-reinforced cementitious matrix (FRCM) systems. The purpose of this paper is to evaluate the behavior of reinforced concrete (RC) beams strengthened in shear with U-wraps made of FRCM. An extensive experimental program was undertaken in order to understand and characterize this composite when used as a strengthening system. The laboratory results demonstrate the technical viability of FRCM for shear strengthening of RC beams. Based on the experimental and analytical results, FRCM increases shear strength but not proportionally to the number of fabric plies installed. On the other hand, FRCM failure modes are related with a high consistency to the amount of external reinforcement applied. Design considerations based on the algorithms proposed by ACI guidelines are also provided.

The present invention relates to a method for preparing synthetic shaped cementitious compositions having high quality even without the addition of high energy binders, such as portland cement, through the use of the spent residue from a fluidized combustion bed of the type wherein limestone particles are suspended in a fluidized medium and sulfur oxides are captured, and pulverized coal fly ash.

The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.

Modeling is essential to integrating knowledge of human physiology. Comprehensive self-consistent descriptions expressed in quantitative mathematical form define working hypotheses in testable and reproducible form, and though such models are always “wrong” in the sense of being incomplete or partly incorrect, they provide a means of understanding a system and improving that understanding. Physiological systems, and models of them, encompass different levels of complexity. The lowest levels concern gene signaling and the regulation of transcription and translation, then biophysical and biochemical events at the protein level, and extend through the levels of cells, tissues and organs all the way to descriptions of integrated systems behavior. The highest levels of organization represent the dynamically varying interactions of billions of cells. Models of such systems are necessarily simplified to minimize computation and to emphasize the key factors defining system behavior; different model forms are thus often used to represent a system in different ways. Each simplification of lower level complicated function reduces the range of accurate operability at the higher level model, reducing robustness, the ability to respond correctly to dynamic changes in conditions. When conditions change so that the complexity reduction has resulted in the solution departing from the range of validity, detecting the deviation is critical, and requires special methods to enforce adapting the model formulation to alternative reduced-form modules or decomposing the reduced-form aggregates to the more detailed lower level modules to maintain appropriate behavior. The processes of error recognition, and of mapping between different levels of model complexity and shifting the levels of complexity of models in response to changing conditions, are essential for adaptive modeling and computer simulation of large-scale systems in reasonable time. PMID:20463841

The SPOT 4 VEGETATION system is a joint program of the European Commission, France, Sweden, Belgium and Italy, to be launched in 1997. It will provide global and frequent measurements adapted to biosphere studies, especially for monitoring of the biophysical processes of the vegetation canopies. Information derived from its measurements will allow operational and long term studies related either to the production of agricultural areas or to the functioning of ecosystems, to their interaction with the atmosphere and climatic changes. The design of the entire system, from the instrument to the ground segment, was aimed at providing direct capability for multitemporal analysis of surface reflectance measurements at medium spatial resolution as well as for association with high spatial resolution data sets available from the SPOT High Resolution instrument or from other systems. Nature and quality of products delivered by the system were especially tailored taking into account the development of research done on previous systems and the needs for characterizing the temporal dynamic aspects of biosphere processes and relating regional or ecosystems' parameters to local parameters less affected by spatial heterogeneity.

A new multireference configuration interaction method using localised orbitals is proposed, in which a molecular system is divided into regions of unequal importance. The advantage of dealing with local orbitals, i.e., the possibility to neglect long range interaction is enhanced. Indeed, while in the zone of the molecule where the important phenomena occur, the interaction cut off may be as small as necessary to get relevant results, in the most part of the system it can be taken rather large, so that results of good quality may be obtained at a lower cost. The method is tested on several systems. In one of them, the definition of the various regions is not based on topological considerations, but on the nature, σ or π, of the localised orbitals, which puts in evidence the generality of the approach. PMID:22979845

A new multireference configuration interaction method using localised orbitals is proposed, in which a molecular system is divided into regions of unequal importance. The advantage of dealing with local orbitals, i.e., the possibility to neglect long range interaction is enhanced. Indeed, while in the zone of the molecule where the important phenomena occur, the interaction cut off may be as small as necessary to get relevant results, in the most part of the system it can be taken rather large, so that results of good quality may be obtained at a lower cost. The method is tested on several systems. In one of them, the definition of the various regions is not based on topological considerations, but on the nature, σ or π, of the localised orbitals, which puts in evidence the generality of the approach.

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by

technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

A signal processing approach is proposed to jointly filter and fuse spatially indexed measurements captured from many vehicles. It is assumed that these measurements are influenced by both sensor noise and measurement indexing uncertainties. Measurements from low-cost vehicle-mounted sensors (e.g., accelerometers and Global Positioning System (GPS) receivers) are properly combined to produce higher quality road roughness data for cost-effective road surface condition monitoring. The proposed algorithms are recursively implemented and thus require only moderate computational power and memory space. These algorithms are important for future road management systems, which will use on-road vehicles as a distributed network of sensing probes gathering spatially indexed measurements for condition monitoring, in addition to other applications, such as environmental sensing and/or traffic monitoring. Our method and the related signal processing algorithms have been successfully tested using field data.

In FY2013, the Cementitious Barriers Partnership (CBP) demonstrated continued tangible progress toward fulfilling the objective of developing a set of software tools to improve understanding and prediction of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. In November 2012, the CBP released “Version 1.0” of the CBP Software Toolbox, a suite of software for simulating reactive transport in cementitious materials and important degradation phenomena. In addition, the CBP completed development of new software for the “Version 2.0” Toolbox to be released in early FY2014 and demonstrated use of the Version 1.0 Toolbox on DOE applications. The current primary software components in both Versions 1.0 and 2.0 are LeachXS/ORCHESTRA, STADIUM, and a GoldSim interface for probabilistic analysis of selected degradation scenarios. The CBP Software Toolbox Version 1.0 supports analysis of external sulfate attack (including damage mechanics), carbonation, and primary constituent leaching. Version 2.0 includes the additional analysis of chloride attack and dual regime flow and contaminant migration in fractured and non-fractured cementitious material. The LeachXS component embodies an extensive material property measurements database along with chemical speciation and reactive mass transport simulation cases with emphasis on leaching of major, trace and radionuclide constituents from cementitious materials used in DOE facilities, such as Saltstone (Savannah River) and Cast Stone (Hanford), tank closure grouts, and barrier concretes. STADIUM focuses on the physical and structural service life of materials and components based on chemical speciation and reactive mass transport of major cement constituents and aggressive species (e.g., chloride, sulfate, etc.). THAMES is a planned future CBP Toolbox component focused on simulation of the microstructure of cementitious materials and calculation of resultant

Ground Penetrating Radar (GPR) systems are worth to be considered as in situ non invasive diagnostic tools capable of assessing stability and integrity of transport infrastructures. As a matter of fact, by exploiting the interactions among probing electromagnetic waves and hidden objects, they provide images of the inner status of the spatial region under test from which infer risk factors, such as deformations and oxidization of the reinforcement bars as well as water infiltrations, crack and air gaps. With respect to the assessment of concrete infrastructures integrity, the reconstruction capabilities of GPR systems have been widely investigated [1,2]. However, the demand for diagnostic tools capable of providing detailed and real time information motivates the design and the performance evaluation of novel technologies and data processing methodologies aimed not only to effectively detect hidden anomalies but also to estimate their geometrical features. In this framework, this communication aims at investigating the advantages offered by the joint use of two GPR systems both of them equipped with a specific tomographic imaging approach. The first considered system is a time domain GPR equipped with a 1.5GHz shielded antenna, which is suitable for quick and good resolution surveys of the shallower layers of the structure. As second system, the holographic radar Rascan-4/4000 [3,4] is taken into account, due to its capability of providing holograms of hidden targets from the amplitude of the interference signal arising between the backscattered field and a reference signal. The imaging capabilities of both the GPR tools are enhanced by means of model based data processing approaches, which afford the imaging as a linear inverse scattering problem. Mathematical details on the inversion strategies will be provided at the conference. The combined use of the above GPR systems allows to perform multi-resolution surveys of the region under test, whose aim is, first of

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a

The Northeast Coastal Ocean Forecast System (NECOFS) is a global-regional-estuarine integrated atmosphere/surface wave/ocean forecast model system designed for the northeast US coastal region covering a computational domain from central New Jersey to the eastern end of the Scotian Shelf. The present system includes 1) the mesoscale meteorological model WRF (Weather Research and Forecasting); 2) the regional-domain FVCOM covering the Gulf of Maine/Georges Bank/New England Shelf region (GOM-FVCOM); 3) the unstructured-grid surface wave model (FVCOM-SWAVE) modified from SWAN with the same domain as GOM-FVCOM; 3) the Mass coastal FVCOM with inclusion of inlets, estuaries and intertidal wetlands; and 4) three subdomain wave-current coupled inundation FVCOM systems in Scituate, MA, Hampton River, NH and Mass Bay, MA. GOM-FVCOM grid features unstructured triangular meshes with horizontal resolution of ~ 0.3-25 km and a hybrid terrain-following vertical coordinate with a total of 45 layers. The Mass coastal FVCOM grid is configured with triangular meshes with horizontal resolution up to ~10 m, and 10 layers in the vertical. Scituate, Hampton River and Mass Bay inundation model grids include both water and land with horizontal resolution up to ~5-10 m and 10 vertical layers. GOM-FVCOM is driven by surface forcing from WRF model output configured for the region (with 9-km resolution), the COARE3 bulk air-sea flux algorithm, local river discharges, and tidal forcing constructed by eight constituents and subtidal forcing on the boundary nested to the Global-FVCOM. SWAVE is driven by the same WRF wind field with wave forcing at the boundary nested to Wave Watch III configured for the northwestern Atlantic region. The Mass coastal FVCOM and three inundation models are connected with GOM-FVCOM through one-way nesting in the common boundary zones. The Mass coastal FVCOM is driven by the same surface forcing as GOM-FVCOM. The nesting boundary conditions for the inundation models

Technetium is among the key risk drivers at the Saltstone Facility. The way that it is immobilized in this cementitious waste form is by converting its highly mobile Tc(VII) form to a much less mobile Tc(IV) form through reduction by the cement's blast furnace slag. This report includes a review of published data and experimental results dealing with Tc leaching from Portland cement waste forms. The objectives for the literature study were to document previous reports of Tc interactions with slag-containing cementitious materials. The objectives for the laboratory study were to measure Tc-saltstone Kd values under reducing conditions. From the literature it was concluded: (1) Spectroscopic evidence showed that when Tc(IV) in a slag-cement was exposed to an oxidizing environment, it will convert to the more mobile Tc(VII) species within a short time frame, 2.5 years. (2) SRS saltstone will reduce Tc(VII) in the absence of NaS or sodium dithionite in a reducing atmosphere. (3) Only trace concentrations of atmospheric oxygen (30 to 60 ppm O{sub 2}; Eh 120 mV) at the high pH levels of cementitioussystems is required to maintain Tc as Tc(VII). (4) Experimental conditions must be responsible for wide variability of measured K{sub d} values, such that they are either very low, {approx}1 mL/g, or they are very high {approx}1000 mL/g, suggesting that Tc(VII) or Tc(IV) dominate the systems. Much of this variability appears to be the result of experimental conditions, especially direct controls of oxygen contact with the sample. (5) A field study conducted at SRS in the 1980s indicated that a slag-saltstone immobilized Tc for 2.5 years. Below background concentrations of Tc leached out of the slag-containing saltstone, whereas Tc leached out of the slag-free saltstone at the rate of nitrate loss. One possible explanation for the immobilization of Tc in this study was that the slag-saltstone maintained reducing conditions within the core of the 55-gallon sample, whereas in

While HIV-1 continues to spread, the use of antivirals in preexposure prophylaxis (PrEP) has recently been suggested. Here we present a modular systems pharmacology modeling pipeline, predicting PrEP efficacy of nucleotide reverse transcriptase inhibitors (NRTIs) at the scale of reverse transcription, target-cell, and systemic infection and after repeated viral exposures, akin to clinical trials. We use this pipeline to benchmark the prophylactic efficacy of all currently approved NRTIs in wildtype and mutant viruses. By integrating pharmacokinetic models, we find that intracellular tenofovir-diphosphate builds up too slowly to halt infection when taken "on demand" and that lamivudine may substitute emtricitabine in PrEP combinations. Lastly, we delineate factors confounding clinical PrEP efficacy estimates and provide a method to overcome these. The presented framework is useful to screen and optimize PrEP candidates and strategies and to understand their clinical efficacy by integrating the diverse scales which determine PrEP efficacy. PMID:27439573

To achieve the highest resolution measurement of the physics of magnetic reconnection, the MMS SMART measurements will utilize a high data rate burst storage system for capturing those intervals when the MMS spacecraft traverse important regions of interest. Two basic modes of data taking are planned, Slow Survey and Fast Survey. Fast Survey mode is targeted at the broad regions of the magnetosphere where reconnection can occur. Slow Survey is aimed an regions of secondary science importance. In Fast Survey, all instruments in the SMART suite continually send high rate data to the Central Instrument Data Processor (CIDP) which holds this data in a circular buffer. Along with this data, each instrument sends a burst data quality (BDQ) flag which represents the scientific "quality" of the preceding period for consideration as a burst interval. The CIDP on each spacecraft collects the individual BDQ's and combines them via a predetermined algorithm into a spacecraft data quality (SDQ) flag. Each spacecraft then sends its individual SDQ to the other three spacecraft via the Interspacecraft Ranging and Alarm System (IRAS). After a short latency period all four spacecraft have all four SDQ values and compute a mission data quality (MDQ) flag. If this flag is above the appropriate threshold then all spacecraft save identical data intervals from from the circular buffer for transmission to the ground during the next downlink. If This flexible scheme will yield optimized science data collection and allows the evolution of the burst data criteria as the best burst triggers are identified.

The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M&O 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports.

A general tension-compression-compression (sigmasb1, sigmasb2=sigmasb3) failure criterion for brittle materials is mathematically developed using FEM analysis and experimentally verified by use of the cementitious composite axial tensile test (CCATT). This tensile failure criterion is based on the stress concentration derived from the classical theory of elasticity. This analytical approach shows the upper bound of the tension-compression-compression failure surface for brittle materials. Since the CCATT applies confining hydraulic pressure, a tensile specimen is subjected to triaxial loading defined by the principal stress ratio sigmasb1/|sigmasb2|. When lateral pressure increases, tensile strength decreases; therefore, stress concentration is defined as a function of the principal stress ratio. The model has three distinct regions of behavior corresponding to the principal stress ratio, 0≤sigmasb1/|sigmasb2|<0.9 (high-lateral pressure), 0.9≤sigmasb1/|sigmasb2|<3.0 (medium-lateral pressure), 3.0≤sigmasb1/|sigmasb2| (low-lateral pressure). The experimental failure line shows true tensile strength of cementitious materials under low-lateral pressure. The predicted nominal stress fsb{ta} with large size specimens for the CCATT is written as$fsb{ta}=gamma*{1/{Kt}}*alpha* pwhere gamma$ is the size effect obtained by experimental results; Kt is the stress concentration factor derived from triaxial loading. Tensile strength values from the CCATT are compared to experimental results from other tests such as the uniaxial tensile test and the split cylinder test. CCATT results are analyzed using Weibull theory to measure material reliability and to develop characteristic stresses for construction design. Failure analysis using fractography was conducted on fractured cementitious materials and composites. The failure analysis on test specimens correlated well with FEM stress distributions and with the principal stress ratio. The observed fracture behavior (fracture

We apply the Multi-scale Interferometric Time-series (MInTS) technique, developed at Caltech,to study spatial variations in aseismic creep across the San Andreas, Calaveras and Hayward Faultsystems in Central California.Interferometric Synthetic Aperture Radar (InSAR) Time-series methods estimate the spatio-temporal evolution of surface deformation using multiple SAR interferograms. Traditional time-series analysis techniques like persistent scatterers and short baseline methods assume the statistical independence of InSAR phase measurements over space and time when estimating deformation. However, existing atmospheric phase screen models clearly show that noise in InSAR phase observations is correlated over the spatial domain. MInTS is an approach designed to exploit the correlation of phase observations over space to significantly improve the signal-to-noise ratio in the estimated deformation time-series compared to the traditional time-series InSAR techniques. The MInTS technique reduces the set of InSAR observations to a set of almost uncorrelated observations at various spatial scales using wavelets. Traditional inversion techniques can then be applied to the wavelet coefficients more effectively. Creep across the Central San Andreas Fault and the Hayward Fault has been studied previously using C-band (6 cm wavelength) ERS data, but detailed analysis of the transition zone between the San Andreas and Hayward Faults was not possible due to severe decorrelation. Improved coherence at L-band (24 cm wavelength) significantly improves the spatial coverage of the estimated deformation signal in our ALOS PALSAR data set. We analyze 450 ALOS PALSAR interferograms processed using 175 SAR images acquired between Dec 2006 and Dec 2010 that cover the area along the San Andreas Fault System from Richmond in the San Francisco Bay Area to Maricopa in the San Joaquin Valley.We invert the InSAR phase observations to estimate the constant Line-of-Sight (LOS) deformation

In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing these contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.

In this paper we have worked out on some the complex modeling aspects such as Multi Scale modeling, MATLAB Sugar based modeling and have shown the complexities involved in the analysis of Nano RFID (Radio Frequency Identification) systems. We have shown the modeling and simulation and demonstrated some novel ideas and library development for Nano RFID. Multi scale modeling plays a very important role in nanotech enabled devices properties of which cannot be explained sometimes by abstraction level theories. Reliability and packaging still remains one the major hindrances in practical implementation of Nano RFID based devices. And to work on them modeling and simulation will play a very important role. CNTs is the future low power material that will replace CMOS and its integration with CMOS, MEMS circuitry will play an important role in realizing the true power in Nano RFID systems. RFID based on innovations in nanotechnology has been shown. MEMS modeling of Antenna, sensors and its integration in the circuitry has been shown. Thus incorporating this we can design a Nano-RFID which can be used in areas like human implantation and complex banking applications. We have proposed modeling of RFID using the concept of multi scale modeling to accurately predict its properties. Also we give the modeling of MEMS devices that are proposed recently that can see possible application in RFID. We have also covered the applications and the advantages of Nano RFID in various areas. RF MEMS has been matured and its devices are being successfully commercialized but taking it to limits of nano domains and integration with singly chip RFID needs a novel approach which is being proposed. We have modeled MEMS based transponder and shown the distribution for multi scale modeling for Nano RFID.

Using Discrete-Event Simulation (DES) as a novel paradigm for time integration of large-scale physics-driven systems, we have achieved significant breakthroughs in simulations of multi-dimensional magnetized plasmas where ion kinetic and finite Larmor radius (FLR) and Hall effects play a crucial role. For these purposes we apply a unique asynchronous simulation tool: a parallel, electromagnetic Particle-in-Cell (PIC) code, HYPERS (Hybrid Particle Event-Resolved Simulator), which treats plasma electrons as a charge neutralizing fluid and solves a self-consistent set of non-radiative Maxwell, electron fluid equations and ion particle equations on a structured computational grid. HYPERS enables adaptive local time steps for particles, fluid elements and electromagnetic fields. This ensures robustness (stability) and efficiency (speed) of highly dynamic and nonlinear simulations of compact plasma systems such spheromaks, FRCs, ion beams and edge plasmas. HYPERS is a unique asynchronous code that has been designed to serve as a test bed for developing multi-physics applications not only for laboratory plasma devices but generally across a number of plasma physics fields, including astrophysics, space physics and electronic devices. We have made significant improvements to the HYPERS core: (1) implemented a new asynchronous magnetic field integration scheme that preserves local divB=0 to within round-off errors; (2) Improved staggered-grid discretizations of electric and magnetic fields. These modifications have significantly enhanced the accuracy and robustness of 3D simulations. We have conducted first-ever end-to-end 3D simulations of merging spheromak plasmas. The preliminary results show: (1) tilt-driven relaxation of a freely expanding spheromak to an m=1 Taylor helix configuration and (2) possibility of formation of a tilt-stable field-reversed configuration via merging and magnetic reconnection of two double-sided spheromaks with opposite helicities.

In 1997, the first two United States Department of Energy (US DOE) high level waste tanks (Tanks 17-F and 20-F: Type IV, single shell tanks) were taken out of service (permanently closed) at the Savannah River Site (SRS). In 2012, the DOE plans to remove from service two additional Savannah River Site (SRS) Type IV high-level waste tanks, Tanks 18-F and 19-F. These tanks were constructed in the late 1950's and received low-heat waste and do not contain cooling coils. Operational closure of Tanks 18-F and 19-F is intended to be consistent with the applicable requirements of the Resource Conservation and Recovery Act (RCRA) and the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and will be performed in accordance with South Carolina Department of Health and Environmental Control (SCDHEC). The closure will physically stabilize two 4.92E+04 cubic meter (1.3 E+06 gallon) carbon steel tanks and isolate and stabilize any residual contaminants left in the tanks. Ancillary equipment abandoned in the tanks will also be filled to the extent practical. A Performance Assessment (PA) has been developed to assess the long-term fate and transport of residual contamination in the environment resulting from the operational closure of the F-Area Tank Farm (FTF) waste tanks. Next generation flowable, zero-bleed cementitious grouts were designed, tested, and specified for closing Tanks 18-F and 19-F and for filling the abandoned equipment. Fill requirements were developed for both the tank and equipment grouts. All grout formulations were required to be alkaline with a pH of 12.4 and to be chemically reducing with a reduction potential (Eh) of -200 to -400. Grouts with this chemistry stabilize potential contaminants of concern. This was achieved by including Portland cement and Grade 100 slag in the mixes, respectively. Ingredients and proportions of cementitious reagents were selected and adjusted to support the mass placement strategy developed by

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the

We show how the rheological response of a material to applied loads can be systematically coded, analyzed and succinctly summarized, according to an individual grain's property (e.g. kinematics). Individual grains are considered as their own smart sensor akin to microelectromechanical systems (e.g. gyroscopes, accelerometers), each capable of recognizing their evolving role within self-organizing building block structures (e.g. contact cycles and force chains). A symbolic time series is used to represent their participation in such self-assembled building blocks and a complex network summarizing their interrelationship with other grains is constructed. In particular, relationships between grain time series are determined according to the information theory Hamming distance or the metric Euclidean distance. We then use topological distance to find network communities enabling groups of grains at remote physical metric distances in the material to share a classification. In essence grains with similar structural and functional roles at different scales are identified together. This taxonomy distills the dissipative structural rearrangements of grains down to its essential features and thus provides pointers for objective physics-based internal variable formalisms used in the construction of robust predictive continuum models.

ITER and next-step devices will have harsh neutron environment and limited port space, severely restricting many crucial plasma diagnostics. As such, it is essential that we develop robust diagnostics with minimal access restrictions, small port requirements, and high spatiotemporal bandwidths. DIII-D's Phase Contrast Imaging (PCI) system is a model of such a burning plasma diagnostic, using a 10.6 μ m laser to measure ∫ñe dl at 10 kHz < f < 10 MHz and 1.5 cm-1 < k < 30 cm-1. To eliminate PCI's low- k cutoff, we have designed and are constructing a traditional interferometer along the existing PCI beam path, extending the minimum detectable k to 0 cm-1. The combined PCI-interferometer uses a single 10.6 μ m beam, two interference schemes, and two detectors to make the relevant measurements. In addition to diagnostic proof-of-principle, the combined PCI-interferometer's improved bandwidth will aid model validation and allow measurement of low and high n MHD modes. Initial results will be discussed. Work supported by the US DOE under DE-FG02-94ER54235, DE-FC02-04ER54698, DE-FC02-99ER54512, and NNSA SSGF.

To advance solutions needed for remediation of DOE contaminated sites, approaches are needed that can elucidate and predict reactions associated with coupled biological, geochemical, and hydrological processes over a variety of spatial scales and in heterogeneous environments. Our laboratory experimental experiments, which were conducted under controlled conditions, suggest that geophysical methods have the potential for elucidating system transformations that often occur during remediation, such as the generation of gases and precipitates. In this new ERSP project, we will Integrate hydrological, biogeochemical, and geophysical expertise and approaches to: (1) Explore the potential of geophysical methods for detecting changes in physical, chemical, and biological properties at the field scale; and (2) Explore the joint use of reactive transport modeling and geophysical monitoring information for improvements in both methods. A brief review of our previously-conducted laboratory results are given in Section II. Section III describes the approach for our new project, which will have both laboratory and field-scale components. The field scale component will be conducted at the Rifle, CO. site, which is described in Section IV.

We have investigated the dynamics of Newtonian fluids with viscosities (10-1000 Pa s; corresponding to mafic to intermediate silicate melts) during slow decompression, in a Plexiglas shock tube. As an analogue fluid we used silicon oil saturated with Argon gas for 72 hours. Slow decompression, dropping from 10 MPa to ambient pressure, acts as the excitation mechanism, initiating several processes with their own distinct timescales. The evolution of this multi-timescale phenomenon generates complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit. Correlation analysis of these time series with the associated high-speed imaging enables characterization of distinct phases of the dynamics of these viscous fluids and the extraction of the time and the frequency characteristics of the individual processes. We have identified fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution in space. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the system. Our observations point to the great potential of this experimental approach in the understanding of volcanic processes and volcanic seismicity.

A comprehensive analysis of the major features of the Asian monsoon system in the NCEP Climate Forecast System version 2 (CFSv2) and predictions of the monsoon by the model has been conducted. The intraseasonal-to-interannual variations of both summer monsoon and winter monsoon, as well as the annual cycles of monsoon climate, are focused. Features of regional monsoons including the monsoon phenomena over South Asia, East Asia, and Southeast Asia are discussed. The quasi-biweekly oscillation over tropical Asia and the Mei-yu climate over East Asia are also investigated. Several aspects of monsoon features including the relationships between monsoon and ENSO (including different types of ENSO: eastern Pacific warming and central Pacific warming), extratropical effects, dependence on time leads (initial conditions), regional monsoon features, and comparison between CFSv2 and CFS version 1 (CFSv1) are particularly emphasized. Large-scale characteristics of the Asian summer monsoon including several major dynamical monsoon indices and their associated precipitation patterns can be predicted several months in advance. The skill of predictions of the monsoon originates mostly from the impact of ENSO. It is found that large predictability errors occur in first three lead months and they only change slightly as lead time increases. The large errors in the first three lead months are associated with the large errors in surface thermal condition and atmospheric circulation in the central and eastern Pacific and the African continent. In addition, the response of the summer monsoon to ENSO becomes stronger with increase in lead time. The CFSv2 successfully simulates several major features of the East Asian winter monsoon and its relationships with the Arctic Oscillation, the East Asian subtropical jet, the East Asian trough, the Siberian high, and the lower-tropospheric winds. Surprisingly, the upper-tropospheric winds over the middle-high latitudes can be better simulated

Grout is used to seal the annulus between the borehole and heat exchanger loops in vertical geothermal (ground coupled, ground source, GeoExchange) heat pump systems. The grout provides a heat transfer medium between the heat exchanger and surrounding formation, controls groundwater movement and prevents contamination of water supply. Enhanced heat pump coefficient of performance (COP) and reduced up-front loop installation costs can be achieved through optimization of the grout thermal conductivity. The objective of the work reported was to characterize thermal conductivity and other pertinent properties of conventional and filled cementitious grouts. Cost analysis and calculations of the reduction in heat exchanger length that could be achieved with such grouts were performed by the University of Alabama. Two strategies to enhance the thermal conductivity of cementitious grouts were used simultaneously. The first of these was to incorporate high thermal conductivity filler in the grout formulations. Based on previous tests (Allan and Kavanaugh, in preparation), silica sand was selected as a suitable filler. The second strategy was to reduce the water content of the grout mix. By lowering the water/cement ratio, the porosity of the hardened grout is decreased. This results in higher thermal conductivity. Lowering the water/cement ratio also improves such properties as permeability, strength, and durability. The addition of a liquid superplasticizer (high range water reducer) to the grout mixes enabled reduction of water/cement ratio while retaining pumpability. Superplasticizers are commonly used in the concrete and grouting industry to improve rheological properties.

Abstract In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.

We propose the description of fracture-fault systems in terms of a multi-scale hierarchical network. In most generic form, such arrangement is referred to as a structural fabric and applicable across the length scale spectrum. The statistical characterisation combines the fracture length and orientation distributions and intersection-termination relationships. The aim is a parameterised description of the network that serves as input in stochastic network simulations that should reproduce the essence of natural fracture networks and encompass its variability. The quality of the stochastically generated fabric is determined by comparison with deterministic descriptions on which the model parameterisation is based. Both the deterministic and stochastic derived fracture network description can serve as input in fluid flow or mechanical simulations that accounts explicitly for the discrete features and the response of the system can be compared. The deterministic description of our current study in the framework of tight gas reservoirs is obtained from coastal pavements that expose a horizontal slice through a fracture-fault network system in fine grained sediments in Yorkshire, UK. Fracture hierarchies have often been described at one observation scale as a two-tier hierarchy in terms of 1st order systematic joints and 2nd order cross-joints. New in our description is the bridging between km-sized faults with notable displacement down to sub-meter scale shear and opening mode fractures. This study utilized a drone to obtain cm-resolution imagery of pavements from ~30m altitude and the large coverage up to 1-km by flying at a ~80m. This unique set of images forms the basis for the digitizing of the fracture-fault pattern and helped determining the nested nature of the network as well as intersection and abutment relationships. Fracture sets were defined from the highest to lowest hierarchical order and probability density functions were defined for the length

Durability assessment of concrete structures for constructions in nuclear waste repositories requires long term service life predictions. As deposition of low and intermediate level radioactive waste (LILW) takes up to 100 000 years, it is necessary to analyze the service life of cementitious materials in this time perspective. Using acceleration methods producing aged specimens would decrease the need of extrapolating short term data sets. Laboratory methods are therefore, needed for accelerating the ageing process without making any influencing distortion in the properties of the materials. This paper presents an electro-chemical migration method to increase the rate of calcium leaching from cementitious specimens. This method is developed based on the fact that major long term deterioration process of hardened cement paste in concrete structures for deposition of LILW is due to slow diffusion of calcium ions. In this method the cementitious specimen is placed in an electrochemical cell as a porous path way through which ions can migrate at a rate far higher than diffusion process. The electrical field is applied to the cell in a way to accelerate the ion migration without making destructions in the specimen's micro and macroscopic properties. The anolyte and catholyte solutions are designed favoring dissolution of calcium hydroxide and compensating for the leached calcium ions with another ion like lithium.

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

Grand Canonical Monte Carlo methods in conjunction with continuum Multiscale simulation to estimate the hydration energies and surface potentials of silver halides as demonstrated elsewhere is employed by incorporating random distribution of molecules, nearest neighbor distances and hydration numbers. The extent of dehydration during each step and the corresponding variation in the hydration numbers are evaluated, assuming the validity of hard spheres. These estimates are then employed to deduce the redox potential of the reaction viz. 2AgX(solution)⇔2Ag(solid)+X2(gas). The dependence of these values on the nature of the halides and solvation characteristics is indicated. PMID:27442589

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

The objective of this study was to measure Tc sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. Earlier studies were conducted and the experimental conditions were found not to simulate those of the facility. Through a five month subcontract with Clemson University, sorption of {sup 99}Tc to four cementitious materials was examined within an anaerobic glovebag targeting a 0.1% H2(g)/ 99.9% N{sub 2}(g) atmosphere. Early experiments based on Tc sorption and Eh indicated that 0.1% H{sub 2}(g) (a reductant) was necessary to preclude experimental impacts from O{sub 2}(g) diffusion into the glovebag. Preliminary data to date (up to 56 days) indicates that sorption of {sup 99}Tc to cementitious materials increased with increasing slag content for simulated saltstone samples. This is consistent with the conceptual model that redox active sulfide groups within the reducing slag facilitate reduction of Tc(VII) to Tc(IV). These experiments differ from previous experiments where a 2% H{sub 2}(g) atmosphere was maintained (Kaplan et al., 2011 (SRNL-STI-2010-00668)). The impact of the 2% H{sub 2}(g) reducing atmosphere on this data was examined and determined to cause the reduction of Tc in experimental samples without slag. In the present ongoing study, after 56 days, Tc sorption by the 50-year old cement samples (no slag) was undetectable, whereas Tc sorption in the cementitious materials containing slag continues to increase with contact time (measured after 1, 4, 8, 19 and 56 days). Sorption was not consistent with spike concentrations and steady state has not been demonstrated after 56 days. The average conditional K{sub d} value for the Vault 2 cementitious material was 6,362 mL/g (17% slag), for the TR547 Saltstone (45% slag) the conditional K{sub d} was 1258 mL/g, and for TR545 (90% slag) the conditional K{sub d} was 12,112 mL/g. It is anticipated that additional samples will be collected until steady state

Simulating the turbulence effect on ground telescope observations is of fundamental importance for the design and test of suitable control algorithms for adaptive optics systems. In this paper we propose a multiscale approach for efficiently synthesizing turbulent phases at very high resolution. First, the turbulence is simulated at low resolution, taking advantage of a previously developed method for generating phase screens [J. Opt. Soc. Am. A 25, 515 (2008)]. Then, high-resolution phase screens are obtained as the output of a multiscale linear stochastic system. The multiscale approach significantly improves the computational efficiency of turbulence simulation with respect to recently developed methods [Opt. Express 14, 988 (2006)] [J. Opt. Soc. Am. A 25, 515 (2008)] [J. Opt. Soc. Am. A 25, 463 (2008)]. Furthermore, the proposed procedure ensures good accuracy in reproducing the statistical characteristics of the turbulent phase. PMID:21772400

In the vicinity of a cementitious nuclear waste repository, mineral reactions will change the hydraulic conditions and the parameters describing radionuclide transport with time during the cement degradation phase. Porosity changes due to mineral and cement reactions will influence permeability and diffusivity. Formation water rich in CO{sub 2} will lead to calcite precipitation in the water-conducting zones surrounding the cementitious waste repository. This will have an impact on the radionuclide release from the cementitious repository into the host rock environment. The sequentially coupled flow, transport, and chemical reaction code MCOTAC is used to include such processes in the modeling. A porosity-permeability relation and a porosity-diffusivity relation are used for describing cement degradation and related secondary mineral precipitation and their coupling to reactive transport modeling. Two-dimensional model calculations are used to predict the temporal evolution of transport parameters for radionuclides within a 'small-scale' near field of a cementitious waste repository. Reduced solute transport is calculated in the repository near field due to porosity and permeability changes at the rock-repository interface. Within the small-scale porous medium approach, coupling of chemical reactions and hydrodynamic parameters indicates a self-sealing barrier at the host rock-repository interface for several scenarios. This barrier might persist for very long times and effectively contain radionuclides within the engineered repository system. Taking into account flow path and barrier-specific heterogeneity will be a further step to improve the understanding of coupled processes in the vicinity of a real cementitious near field.

In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not intended to be comprehensive. We present a general adaptive multiscale model reduction framework, the Generalized Multiscale Finite Element Method. Besides the method's basic outline, we discuss some important ingredients needed for the method's success. We also discuss several applications. The proposed method allows performing local model reduction in the presence of high contrast and no scale separation.

In FY2013, the Cementitious Barriers Partnership (CBP) is continuing in its effort to develop and enhance software tools demonstrating tangible progress toward fulfilling the objective of developing a set of tools to improve understanding and prediction of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. In FY2012, the CBP released the initial inhouse “Beta-version” of the CBP Software Toolbox, a suite of software for simulating reactive transport in cementitious materials and important degradation phenomena. The current primary software components are LeachXS/ORCHESTRA, STADIUM, and a GoldSim interface for probabilistic analysis of selected degradation scenarios. THAMES is a planned future CBP Toolbox component (FY13/14) focused on simulation of the microstructure of cementitious materials and calculation of resultant hydraulic and constituent mass transfer parameters needed in modeling. This past November, the CBP Software Toolbox Version 1.0 was released that supports analysis of external sulfate attack (including damage mechanics), carbonation, and primary constituent leaching. The LeachXS component embodies an extensive material property measurements database along with chemical speciation and reactive mass transport simulation cases with emphasis on leaching of major, trace and radionuclide constituents from cementitious materials used in DOE facilities, such as Saltstone (Savannah River) and Cast Stone (Hanford), tank closure grouts, and barrier concretes. STADIUM focuses on the physical and structural service life of materials and components based on chemical speciation and reactive mass transport of major cement constituents and aggressive species (e.g., chloride, sulfate, etc.). The CBP issued numerous reports and other documentation that accompanied the “Version 1.0” release including a CBP Software Toolbox User Guide and Installation Guide. These documents, as well as, the

Crack damages due to load application are commonly observed in cementitious granular materials such as concrete, cemented sand, and ceramic materials. Previous analytical models for these types of materials have been developed based on continuum mechanics using a phenomenological approach. However, the theories of continuum mechanics have limitations when used for analyzing fracture mechanism and localized damages at a micro-scale level. Therefore, a microstructural approach is desirable for the analysis of these types of materials. In this dissertation, a contact law was derived for the inter-particle behavior of two particles connected by a cement binder. Microcracking process within binder was fully taken into account by regarding crack length as a basic damage factor. The binder initially contains small-size cracks which propagate and grow under external loading. As a result the binder is weakened with lower strength in shear and tension. Theory of fracture mechanics was employed to model the propagation and growth of these microcracks for both the shear fracture mode and normal fracture mode. The contact law was then incorporated in the analysis for the overall damage behaviors of cementitious granular material using the statistical micromechanics approach and the distinct element method. These overall damage behaviors include the stress-strain relationship, fracture strength, development of damage zone, and fatigue deformation. The micro-parameters affecting these behaviors are mainly the microcrack length and density, binder toughness, and binder elastic constants. In the numerical simulations, the cementitious granular materials were represented by 2-D random assemblies of rods bonded by cement binders with preexisting microcracks. Stress-strain relationships were modeled and validated for the uniaxial tension and compression tests, biaxial tension and compression tests, and double cantilever beam test. Force-deflection relationship and fatigue deformation

The setting and development of strength of Portland cement concrete depends upon the reaction of water with various phases in the Portland cement. Nuclear resonance reaction analysis (NRRA) involving the (1)H((15)N,alpha,gamma)(12)C reaction has been applied to measure the hydrogen depth profile in the few 100 nm thick surface layer that controls the early stage of the reaction. Specific topics that have been investigated include the reactivity of individual cementitious phases and the effects of accelerators and retarders. PMID:19931465

The alkaline activation of aluminosiliceous industrial by-products such as blast furnace slag and fly ash is widely known to yield binders whose properties make them comparable to or even stronger and more durable than ordinary Portland cement. The present paper discusses activation fundamentals (such as the type and concentration of alkaline activator and curing conditions) as well as the structure of the cementitious gels formed (C-A-S-H, N-A-S-H). The durability and strength of these systems make these materials apt for use in many industrial applications, such as precast concrete elements (masonery blocks, railroad sleepers), protective coatings for materials with low fire ratings and lightweight elements.

Multiscale modeling of stochastic systems, or uncertainty quantization of multiscale modeling is becoming an emerging research frontier, with rapidly growing engineering applications in nanotechnology, biotechnology, advanced materials, and geo-systems, etc. While tremendous efforts have been devoted to either stochastic methods or multiscale methods, little combined work had been done on integration of multiscale and stochastic methods, and there was no method formally available to tackle multiscale problems involving uncertainties. By developing an innovative Multiscale Stochastic Finite Element Method (MSFEM), this research has made a ground-breaking contribution to the emerging field of Multiscale Stochastic Modeling (MSM) (Fig 1). The theory of MSFEM basically decomposes a boundary value problem of random microstructure into a slow scale deterministic problem and a fast scale stochastic one. The slow scale problem corresponds to common engineering modeling practices where fine-scale microstructure is approximated by certain effective constitutive constants, which can be solved by using standard numerical solvers. The fast scale problem evaluates fluctuations of local quantities due to random microstructure, which is important for scale-coupling systems and particularly those involving failure mechanisms. The Green-function-based fast-scale solver developed in this research overcomes the curse-of-dimensionality commonly met in conventional approaches, by proposing a random field-based orthogonal expansion approach. The MSFEM formulated in this project paves the way to deliver the first computational tool/software on uncertainty quantification of multiscalesystems. The applications of MSFEM on engineering problems will directly enhance our modeling capability on materials science (composite materials, nanostructures), geophysics (porous media, earthquake), biological systems (biological tissues, bones, protein folding). Continuous development of MSFEM will

Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscalesystems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscalesystems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.

The work presented in this dissertation is aimed to implement and further develop the recent advances in material characterization for porous and heterogeneous materials and apply these advances to sustainable concretes. The studied sustainable concretes were concrete containing fly ash and slag, Kenaf fiber reinforced concrete, and lightweight aggregate concrete. All these cement-based materials can be categorized as sustainable concrete, by achieving concrete with high strength while reducing cement consumption. The nanoindentation technique was used to infer the nanomechanical properties of the active hydration phases in bulk cement paste. Moreover, the interfacial transition zone (ITZ) of lightweight aggregate, normal aggregate, and Kenaf fibers were investigated using nanoindentation and imagine techniques, despite difficulties regarding characterizing this region. Samples were also tested after exposure to high temperature to evaluate the damage mechanics of sustainable concretes. It has been shown that there is a direct correlation between the nature of the nanoscale structure of a cement-based material with its macroscopic properties. This was addressed in two steps in this dissertation: (i) Nanoscale characterization of sustainable cementitious materials to understand the different role of fly ash, slag, lightweight aggregate, and Kenaf fibers on nanoscale (ii) Link the nanoscale mechanical properties to macroscale ones with multiscale modeling. The grid indentation technique originally developed for normal concrete was extended to sustainable concretes with more complex microstructure. The relation between morphology of cement paste materials and submicron mechanical properties, indentation modulus, hardness, and dissipated energy is explained in detail. Extensive experimental and analytical approaches were focused on description of the materials' heterogeneous microstructure as function of their composition and physical phenomenon. Quantitative

Segmentation and classification are prolific research topics in the image processing community. These topics have been increasingly used in the context of analysis of cementitious materials on images acquired with a scanning electron microscope. Indeed, there is a need to be able to detect and to quantify the materials present in a cement paste in order to follow the chemical reactions occurring in the material even days after the solidification. We propose a new approach for segmentation and classification of cementitious materials based on the denoising of the data with a block-matching three-dimensional (3-D) algorithm, binary partition tree (BPT) segmentation, support vector machines (SVM) classification, and interactivity with the user. The BPT provides a hierarchical representation of the spatial regions of the data, allowing a segmentation to be selected among the admissible partitions of the image. SVMs are used to obtain a classification map of the image. This approach combines state-of-the-art image processing tools with user interactivity to allow a better segmentation to be performed, or to help the classifier discriminate the classes better. We show that the proposed approach outperforms a previous method when applied to synthetic data and several real datasets coming from cement samples, both qualitatively with visual examination and quantitatively with the comparison of experimental results with theoretical ones.

One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to

The Saltstone facilities at the DOE Savannah River Site (SRS) stabilize and dispose of low-level radioactive salt solution originating from liquid waste storage tanks at the site. The Saltstone Production Facility (SPF) receives treated salt solution and mixes the aqueous waste with dry cement, blast furnace slag, and fly ash to form a grout slurry which is mechanically pumped into concrete disposal cells that compose the Saltstone Disposal Facility (SDF). The solidified grout is termed “saltstone”. Cementitious materials play a prominent role in the design and long-term performance of the SDF. The saltstone grout exhibits low permeability and diffusivity, and thus represents a physical barrier to waste release. The waste form is also reducing, which creates a chemical barrier to waste release for certain key radionuclides, notably Tc-99. Similarly, the concrete shell of an SDF disposal unit (SDU) represents an additional physical and chemical barrier to radionuclide release to the environment. Together the waste form and the SDU compose a robust containment structure at the time of facility closure. However, the physical and chemical state of cementitious materials will evolve over time through a variety of phenomena, leading to degraded barrier performance over Performance Assessment (PA) timescales of thousands to tens of thousands of years. Previous studies of cementitious material degradation in the context of low-level waste disposal have identified sulfate attack, carbonation influenced steel corrosion, and decalcification (primary constituent leaching) as the primary chemical degradation phenomena of most relevance to SRS exposure conditions. In this study, degradation time scales for each of these three degradation phenomena are estimated for saltstone and concrete associated with each SDU type under conservative, nominal, and best estimate assumptions. The nominal value (NV) is an intermediate result that is more probable than the conservative

The objective of this study was to measure Tc sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. Earlier studies were conducted and the experimental conditions were found not to simulate those of the facility. Through a five month subcontract with Clemson University, sorption of {sup 99}Tc to four cementitious materials was examined within an anaerobic glovebag targeting a 0.1% H{sub 2}(g)/ 99.9% N{sub 2}(g) atmosphere. Early experiments based on Tc sorption and Eh indicated that 0.1% H{sub 2}(g) (a reductant) was necessary to preclude experimental impacts from O{sub 2}(g) diffusion into the glovebag. Preliminary data to date (up to 56 days) indicates that sorption of {sup 99}Tc to cementitious materials increased with increasing slag content for simulated saltstone samples. This is consistent with the conceptual model that redox active sulfide groups within the reducing slag facilitate reduction of Tc(VII) to Tc(IV). These experiments differ from previous experiments where a 2% H{sub 2}(g) atmosphere was maintained (Kaplan et al., 2011 (SRNL-STI-2010-00668)). The impact of the 2% H{sub 2}(g) reducing atmosphere on this data was examined and determined to cause the reduction of Tc in experimental samples without slag. In the present ongoing study, after 56 days, Tc sorption by the 50-year old cement samples (no slag) was undetectable, whereas Tc sorption in the cementitious materials containing slag continues to increase with contact time (measured after 1, 4, 8, 19 and 56 days). Sorption was not consistent with spike concentrations and steady state has not been demonstrated after 56 days. The average conditional K{sub d} value for the Vault 2 cementitious material was 873 mL/g (17% slag), for the TR547 Saltstone (45% slag) the conditional K{sub d} was 168 mL/g, and for TR545 (90% slag) the conditional K{sub d} was 1,619 mL/g. It is anticipated that additional samples will be collected until steady state

Unique amorphous alloys are synthesized at the compositions of 25 and 40 atom % of W by ion beam mixing in the equilibrium immiscible Sc-W system characterized by a positive heat of formation of +14 kJ/mol. In thermodynamic modeling, a Gibbs free energy diagram is constructed based on Miedema's theory, and the diagram predicts a glass-forming range of the Sc-W system to be within 12-58 atom % of W. To develop an atomistic model, ab initio calculations are first conducted to assist the construction of an n-body Sc-W potential under the embedded atom method. The proven realistic potential is applied in molecular dynamic simulations to study the crystal-to-amorphous transition in the Sc-W solid solutions, thus determining the glass-forming ability of the system to be within 15-50 atom % of W. Apparently, both theoretical predicted glass-forming ranges cover the experimentally measured one, showing an excellent agreement. We report, in this paper, the experimental results from ion beam mixing and the multiscale theoretical modeling concerning the amorphous alloy formation in the Sc-W system together with a brief discussion of the structural transition mechanism. PMID:16851507

Recent scientific work underlined the presence of a thick Cenozoic infill in the Levant Basin reaching up to 12 km. Interestingly; restricted sedimentation was observed along the Levant margin in the Cenozoic. Since the Late Eocene successive regional geodynamic events affecting Afro-Arabia and Eurasia (collision and strike slip deformation)induced fast marginal uplifts. The initiation of local and long-lived regional drainage systems in the Oligo-Miocene period (e.g. Lebanon versus Nile) provoked a change in the depositional pattern along the Levant margin and basin. A shift from carbonate dominated environments into clastic rich systems has been observed. Through this communication we explore the importance of multi-scale constraints (i.e.,seismic, well and field data) in the quantification of the subsidence history, sediment transport and deposition of a Middle-Upper Miocene "multi-source" to sink system along the northernLevant frontier region. We prove through a comprehensive forward stratigraphic modeling workflow that the contribution to the infill of the northern Levant Basin (offshore Lebanon) is split in between proximal and more distal clastic sources as well as in situ carbonate/hemipelagic deposition. In a wider perspective this work falls under the umbrella of multi-disciplinary source to sink studies that investigate the impact of geodynamic events on basin/margin architectural evolutions, consequent sedimentary infill and thus on petroleum systems assessment.

Encoding information about continuous variables using noisy computational units is a challenge; nonetheless, asymptotic theory shows that combining multiple periodic scales for coding can be highly precise despite the corrupting influence of noise [Mathis, Herz, and Stemmler, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.109.018103 109, 018103 (2012)]. Indeed, the cortex seems to use periodic, multiscale grid codes to represent position accurately. Here we show how such codes can be read out without taking the long-term limit; even on short time scales, the precision of such codes scales exponentially in the number N of neurons. Does this finding also hold for neurons that are not firing in a statistically independent fashion? To assess the extent to which biological grid codes are subject to statistical dependences, we first analyze the noise correlations between pairs of grid code neurons in behaving rodents. We find that if the grids of two neurons align and have the same length scale, the noise correlations between the neurons can reach values as high as 0.8. For increasing mismatches between the grids of the two neurons, the noise correlations fall rapidly. Incorporating such correlations into a population coding model reveals that the correlations lessen the resolution, but the exponential scaling of resolution with N is unaffected.

The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers'' (BSC 2004 [DIRS 170033]); (6) ''Ventilation Model and Analysis Report'' (BSC 2004 [DIRS 169862]); (7) ''Heat Capacity

Traditionally ultrasonic testing is used to estimate the extent of damage in a concrete structure. However Pulse-velocity and amplitude attenuation methods are not very reliable, and are difficult to reveal early damage of concrete. In a previous study, a new active modulation approach, Nonlinear Active Wave Modulation Spectroscopy, was developed and found promising for early detection of damage in concrete. In this procedure, a probe wave is passed through the system in a fashion similar to regular acoustic methods for inspection. Simultaneously, a second, low-frequency modulating wave is applied to the system to effectively change the size and stiffness of flaws microscopically and cyclically, thereby causing the frequency modulation to change cyclically as well. It has been also shown that it is advantageous to apply the Hilbert-Huang transform to decompose nonlinear non-stationary time-domain responses of plain concrete. Such procedure leads to improving the damage detection sensitivity of this modulation method in concrete. In this paper, further investigation on mortar and fiber reinforced concrete will be presented and discussed.

Given the non competition of miscanthus with food and animal feed, this lignocellulosic species has attracted attention as a possible biofuel resource. However, sustainability of ethanol production from lignocelluloses biomass would imply reduction in the consumption of chemicals and/or energetic means, but also valorization of the lignocellulosic by-product remaining from enzymatic saccharification. Introduction of these by-products into a cementitious matrix could be used in manufacturing a lightweight composite. Miscanthus biomass was submitted to chemical pretreatments followed by saccharification using an enzymatic cocktail. Residues from saccharification were then mixed with a cementitious matrix. Given their mechanical properties and a good adherence between cement and by-product, the hardened materials could be used. However, the delay in the beginning of setting time is too long, which prevents the direct use of by-product into cementitious matrix. Preliminary experiments using a setting accelerator in the cementitious matrix permitted significant reduction in the setting time delay. PMID:22078741

Iron oxide has been considered a promising host for immobilizing and encapsulating radioactive 99Tc (t1/2=2.1x105 year), which significantly enhances the stability of 99Tc within a cementitious waste form. However, the flow behavior of cementitious slurry containing iron oxide has never been investigated to ensure its workability, which directly influences the preparation and performance of the cementitious waste form monolith. Variation in the rheological properties of the cementitious slurry were studied using rheometry and ultrasonic wave reflection to understand the effects of various iron oxides (magnetite, hematite, ferrihydrite, and goethite) during the cement setting and stiffening processes. The rheological behavior significantly varied with the addition of different chemical compounds of iron oxides. Complementary microscopic characteristics such as colloidal vibration currents, morphology, and particle size distributions further suggest that the most adverse alteration of cement setting and stiffening behavior caused by the presence of goethite may be attributed to its acicular shape.

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system’s pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute. PMID:26792977

Salt loadings approaching 50 wt % were tolerated in cementitious waste forms that still met leach and strength criteria, addressing a Technology Deficiency of low salt loadings previously identified by the Mixed Waste Focus Area. A statistical design quantified the effect of different stabilizing ingredients and salt loading on performance at lower loadings, allowing selection of the more effective ingredients for studying the higher salt loadings. In general, the final waste form needed to consist of 25 wt % of the dry stabilizing ingredients to meet the criteria used and 25 wt % water to form a workable paste, leaving 50 wt % for waste solids. The salt loading depends on the salt content of the waste solids but could be as high as 50 wt % if all the waste solids are salt.

We discuss concurrent multiscale simulations of dynamic and temperature-dependent processes found in nanomechanical systems coupled to larger scale surroundings. We focus on the behavior of sub-micron Micro-Electro-Mechanical Systems (MEMS), especially micro-resonators. The coupling of length scales methodology we have developed for MEMS employs an atomistic description of small but key regions of the system, consisting of millions of atoms, coupled concurrently to a finite element model of the periphery. The result is a model that accurately describes the behavior of the mechanical components of MEMS down to the atomic scale. This paper reviews some of the general issues involved in concurrent multiscale simulation, extends the methodology to metallic systems and describes how it has been used to identify atomistic effects in sub-micron resonators.

We present the results of a multi-scale analysis of ionospheric TEC fluctuations using a nearly six hour observation of the bright radio source Virgo A with the Very Large Array (VLA) at 74 MHz. Our analysis combines data sensitive to fine-scale structure (~1 km and ~0.001 TECU in amplitude) along the line of sight to Virgo A as well as larger structures (up to hundreds of km) observed using several (~30) moderately bright sources in the field of view. The observations span a time period from midnight to dawn local time during 1 March 2001. MSTIDs are visible intermittently throughout the night, most prominently near dawn. These appear to be mostly directed westward or southwestward with some atypical MSTID-like waves directed toward the north or northwest. Many smaller-scale (between 10 and 50 km) waves are present beginning around 01:30 and are directed toward either the southeast or southwest/west. These are reminiscent of QP-echoes observed with other experiments. The southeastward-directed waves dominate during the beginning of this time period when larger (>50 km) waves are seen moving toward the northwest. As the southwestward/westward-directed QP-echo-like waves begin to dominate around 03:00, the larger waves transition to being predominantly directed toward the west or southwest. The coincidence of these two phenomena may suggest the presence of the direction-dependent E-F coupling instability if the smaller-scale waves are generated within sporadic-E layers. In addition to MSTID- and QP-echo-like waves, we also find evidence of wave-like disturbances as small as ~2 km, most frequently between 02:00 and 04:00. While their sizes and the "Y" pattern of the VLA make their directions difficult to determine, these waves are seen most strongly along antennas in the northern arm of the VLA, suggesting they were roughly traveling in the north-south direction.

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

This report documents the results of testing performed to determine the feasibility of using a pulsed-air mixing technology (equipment developed by Pulsair Systems, Inc., Bellevue, WA) to mix cementitious dry solids with supernatant and settled solids within a horizontal tank. The mixing technology is being considered to provide in situ stabilization of the {open_quotes}V{close_quotes} tanks at the Idaho National Engineering and Environmental Laboratory (INEEL). The testing was performed in a vessel roughly 1/6 the scale of the INEEL tanks. The tests used a fine soil to simulate settled solids and water to simulate tank supernatants. The cementitious dry materials consisted of Portland cement and Aquaset-2H (a product of Fluid Tech Inc. consisting of clay and Portland cement). Two scoping tests were conducted to allow suitable mixing parameters to be selected. The scoping tests used only visual observations during grout disassembly to assess mixing performance. After the scoping tests indicated the approach may be feasible, an additional two mixing tests were conducted. In addition to visual observations during disassembly of the solidified grout, these tests included addition of chemical tracers and chemical analysis of samples to determine the degree of mixing uniformity achieved. The final two mixing tests demonstrated that the pulsed-air mixing technique is capable of producing slurries containing substantially more cementitious dry solids than indicated by the formulations suggested by INEEL staff. Including additional cement in the formulation may have benefits in terms of increasing mobilization of solids, reducing water separation during curing, and increasing the strength of the solidified product. During addition to the tank, the cementitious solids had a tendency to form clumps which broke down with continued mixing.

The multiscale dynamics of complex oxides is illustrated by pairs of mechanical resonances that are excited in the relaxor ferroelectric K1-xLixTaO3 (KLT). These macroscopic resonances are shown to originate in the collective dynamics of piezoelectric polar nanodomains (PNDs) interacting with the surrounding lattice. Their characteristic Fano lineshapes and rapid evolution with temperature reveal the coherent interplay between the piezoelectric oscillations and orientational relaxations of the PNDs at higher temperature and the contribution of heterophase oscillations near the phase transition. A theoretical model is presented, that describes the evolution of the resonances over the entire temperature range. Similar resonances are observed in other relaxors and must therefore be a common characteristics of these systems.

Significant variations of wind power capacity factors (cfs) were observed for turbines across individual wind farms, where the farms span a distance of 10 - 20 km. These variations have a vital impact on power integration and loading. To study these cfs variations, we investigate the inter-farm and intra-farm wind characteristics for farms in northeastern Colorado. This is accomplished by analyzing the wind-farm data, and performing a modeling study using the NCAR Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system. The RTFDDA system, built around the US Weather Research and Forecasting (WRF) model, is capable of continuously collecting and ingesting diverse synoptic and asynoptic weather observations, including WMO standard upper-air and surface reports, wind-profiler data, satellite cloud-drift winds, commercial aircraft reports, all available mesonet/wind-farm weather data, radar observations, and any special instruments that report temperature, winds and moisture. The WRF RTFDDA provides continuous 4-D weather analyses, nowcasts and short-term forecasts. In this study, the WRF-RTFDDA system is run with successive nested domains to simulate the multiscale weather and provide a detailed view of wind circulations at farms. The fine-mesh domains are run at a resolution of 1 - 3 km for spanning the overall environment of wind farms, and ~0.1 - 0.35 km for the study of intra-farm weather features. Fine scale topography (100 m) and land use (30 seconds) data are used to specify the lower boundaries of the fine-mesh domains for simulation of the local underlying forcing. It is well known that the modeling of weather at these scales is a challenge. Thus, a set of sensitivity experiments is conducted to study the impact of available state-of-the-art modeling dynamics, physics and data assimilation schemes on the model performance. The findings will be reported at the meeting.

Under the U.S. NASA and NSF collaborative space weather modeling initiative, a Multimodel Ensemble Prediction System (MEPS) for ionosphere-thermosphere-electrodynamics is being developed. The system includes several Global Assimilative Ionospheric Models (GAIMs) developed by the investigators from Utah State University, Jet Propulsion Laboratory, and University of Southern California. In this study, four GAIMs are applied to a study of ionospheric response to the 17 March 2015 St. Patrick's Day storm. It is the most severe geomagnetic storm in the current solar cycle so far. The daily planetary magnetic Ap index and magnetic Kp, Dst, as well as AE indices reached their very high values, i.e., 108, 8, -202 nT, and 2269 nT, respectively. In the assimilative modeling, GPS data from hundreds of globally-distributed ground stations and a number of COSMIC satellites are assimilated into GAIMs to reproduce ionospheric 3-D volume densities and 2-D total electron content (TEC) during the severe storm. Evolution of strong, latitudinally-dependent, and hemispherically asymmetric ionospheric disturbances is revealed through the assimilative modeling. Using the same GPS data, Global Maps of Ionospheric Irregularities and Scintillation (GMIIS) have also been produced. Comparisons of the modeled large-scale ionospheric disturbances and measured small-scale ionospheric irregularities offer additional insight into the M-I-T coupling processes in different regions during varying storm phases. This presentation will provide a picture of distinguished multi-scale ionospheric response to the coronal mass ejection (CME) event during the major geomagnetic storm.

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut

The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental

Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

In this dissertation, the Perfectly Matched Multiscale Simulations (PMMS), a method of discrete-to-continuum multiscale scale computation is studied, revised and extended. In particular, the role of the Perfectly Matched Layer (PML) in PMMS is carefully studied. We show that instead of following the PML theory of continuum, the PML equations of motion in PMMS can be derived by stretching the inter-atomic equilibrium distance. As a result, the displacement solution in the PML region has the desired spatial damping property. It is also shown that the dispersion relationship in the PML region is different from the one in the original lattice. And a reflection coefficient is computed. We also incorporate the local Quasicontinuum (QC) theory with the cohesive Finite Element (FE) method to form a cohesive QC scheme which can deal with arbitrary discontinuities. This idea is built into the PMMS method to simulate a moving screw dislocation. The second part of the dissertation is to extend PMMS to finite temperature. A multiscale thermodynamics is proposed based on the idea of distributed coarse scale thermostats. Each coarse scale node is viewed as a thermostat and has part of atoms associated with it. The atomic motion at the fine scale level is governed by the Nose-Hoover dynamics. At the coarse scale, the expression of a coarse-grained Helmholtz free energy is derived and coupled thermo-mechanical equations are formulated based on it. With the proposed framework, the finite-temperature PMMS method is capable of simulating problems with drastic temperature change. Several numerical examples are computed to validate the method.

Concrete is heterogeneous at all length scales and its microstructure evolves continuously over decades. Through the use of nanoparticles, it is possible to alter the microstructure of cementitious materials from within the first microsecond to control its rheological and eventual mechanical properties. The continued development of this technology hinges on adopting a materials science approach to achieve proper processing and measurement techniques, both of which are investigated in this study. Novel rheological methods are implemented to evaluate the fresh-state properties of cement pastes modified with nano-sized attapulgite clays. Previous studies have demonstrated that clays can reduce the lateral pressure exerted on formwork by self-consolidating concrete (SCC). It is hypothesized that this is tied to the influence of clays on two rheological properties of SCC: material cohesion and structural rebuilding. Therefore the effect of clays on adhesive properties is measured by the tack test and rate of rebuilding is evaluated by measuring relaxation time during creep. In addition, due to the complexity of cement rheology, i.e. simultaneous thixotropic rebuilding and hydration, the results are supplemented with a measure of the viscoelastic properties obtained through oscillatory shear rheometry. It is found that clays significantly increase cohesion and accelerate structural recovery of cement pastes. The results also indicate that the tack test is a suitable method for measuring the adhesive properties and structural evolution of cementitious materials in the fresh state. The potential of calcium carbonate (CaCO3) nanoparticles in improving the early-age properties of fly ash-cement pastes is investigated. The focus is on dispersing the CaCO3 nanoparticles to enhance their effect and limit the addition level necessary. The selected approach involves sonication in an aqueous medium and use of surfactant. Degree of dispersion and stability are quantitatively

In 1997, the first two United States Department of Energy (US DOE) high level waste tanks (Tanks 17-F and 20-F: Type IV, single shell tanks) were taken out of service (permanently closed) at the Savannah River Site (SRS). In 2012, the DOE plans to remove from service two additional Savannah River Site (SRS) Type IV high-level waste tanks, Tanks 18-F and 19-F. These tanks were constructed in the late 1950's and received low-heat waste and do not contain cooling coils. Operational closure of Tanks 18-F and 19-F is intended to be consistent with the applicable requirements of the Resource Conservation and Recovery Act (RCRA) and the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and will be performed in accordance with South Carolina Department of Health and Environmental Control (SCDHEC). The closure will physically stabilize two 4.92E+04 cubic meter (1.3 E+06 gallon) carbon steel tanks and isolate and stabilize any residual contaminants left in the tanks. The closure will also fill, physically stabilize and isolate ancillary equipment abandoned in the tanks. A Performance Assessment (PA) has been developed to assess the long-term fate and transport of residual contamination in the environment resulting from the operational closure of the F-Area Tank Farm (FTF) waste tanks. Next generation flowable, zero-bleed cementitious grouts were designed, tested, and specified for closing Tanks 18-F and 19-F and for filling the abandoned equipment. Fill requirements were developed for both the tank and equipment grouts. All grout formulations were required to be alkaline with a pH of 12.4 and chemically reduction potential (Eh) of -200 to -400 to stabilize selected potential contaminants of concern. This was achieved by including Portland cement and Grade 100 slag in the mixes, respectively. Ingredients and proportions of cementitious reagents were selected and adjusted, respectively, to support the mass placement strategy developed by closure

Magnetospheric Multiscale (MMS), a NASA four-spacecraft mission scheduled for launch in November 2014, will investigate magnetic reconnection in the boundary regions of the Earth’s magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. Among the important questions about reconnection that will be addressed are the following: Under what conditions can magnetic-field energy be converted to plasma energy by the annihilation of magnetic field through reconnection? How does reconnection vary with time, and what factors influence its temporal behavior? What microscale processes are responsible for reconnection? What determines the rate of reconnection? In order to accomplish its goals the MMS spacecraft must probe both those regions in which the magnetic fields are very nearly antiparallel and regions where a significant guide field exists. From previous missions we know the approximate speeds with which reconnection layers move through space to be from tens to hundreds of km/s. For electron skin depths of 5 to 10 km, the full 3D electron population (10 eV to above 20 keV) has to be sampled at rates greater than 10/s. The MMS Fast-Plasma Instrument (FPI) will sample electrons at greater than 30/s. Because the ion skin depth is larger, FPI will make full ion measurements at rates of greater than 6/s. 3D E-field measurements will be made by MMS once every ms. MMS will use an Active Spacecraft Potential Control device (ASPOC), which emits indium ions to neutralize the photoelectron current and keep the spacecraft from charging to more than +4 V. Because ion dynamics in Hall reconnection depend sensitively on ion mass, MMS includes a new-generation Hot Plasma Composition Analyzer (HPCA) that corrects problems with high proton fluxes that have prevented accurate ion-composition measurements near the dayside magnetospheric boundary. Finally, Energetic Particle Detector (EPD) measurements of electrons and

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO4

Most viruses take advantage of endocytic pathways to gain entry into host cells and initiate infections. Understanding of virus entry via endocytosis is critically important for the design of antiviral strategies. Virus entry via endocytosis is a complex process involving hundreds of cellular proteins. The entire process is dictated by events occurring at multiple time and length scales. In this review, we discuss and evaluate the available means to investigate virus endocytic entry, from both experimental and theoretical/numerical modeling fronts, and highlight the importance of multiscale features. The complexity of the process requires investigations at a systems biology level, which involves the combination of different experimental approaches, the collaboration of experimentalists and theorists across different disciplines, and the development of novel multiscale models. PMID:23734580

The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

This project developed and supported a technology base in nonequilibrium phenomena underpinning fundamental issues in condensed matter and materials science, and applied this technology to selected problems. In this way the increasingly sophisticated synthesis and characterization available for classes of complex electronic and structural materials provided a testbed for nonlinear science, while nonlinear and nonequilibrium techniques helped advance our understanding of the scientific principles underlying the control of material microstructure, their evolution, fundamental to macroscopic functionalities. The project focused on overlapping areas of emerging thrusts and programs in the Los Alamos materials community for which nonlinear and nonequilibrium approaches will have decisive roles and where productive teamwork among elements of modeling, simulations, synthesis, characterization and applications could be anticipated--particularly multiscale and nonequilibrium phenomena, and complex matter in and between fields of soft, hard and biomimetic materials. Principal topics were: (i) Complex organic and inorganic electronic materials, including hard, soft and biomimetic materials, self-assembly processes and photophysics; (ii) Microstructure and evolution in multiscale and hierarchical materials, including dynamic fracture and friction, dislocation and large-scale deformation, metastability, and inhomogeneity; and (iii) Equilibrium and nonequilibrium phases and phase transformations, emphasizing competing interactions, frustration, landscapes, glassy and stochastic dynamics, and energy focusing.

Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

Recently, there has been a dramatic increase in premature deterioration in concrete pavements and flat works that are exposed to chloride based salts. Chloride based salts can cause damage and deterioration in concrete due to the combination of factors which include: increased saturation, ice formation, salt crystallization, osmotic pressure, corrosion in steel reinforcement, and/or deleterious chemical reactions. This thesis discusses how chloride based salts interact with cementitious materials to (1) develop damage in concrete, (2) create new chemical phases in concrete, (3) alter transport properties of concrete, and (4) change the concrete freeze-thaw performance. A longitudinal guarded comparative calorimeter (LGCC) was developed to simultaneously measure heat flow, damage development, and phase changes in mortar samples exposed to sodium chloride (NaCl), calcium chloride (CaCl 2), and magnesium chloride (MgCl2) under thermal cycling. Acoustic emission and electrical resistivity measurements were used in conjunction with the LGCC to assess damage development and electrical response of mortar samples during cooling and heating. A low-temperature differential scanning calorimetry (LT-DSC) was used to evaluate the chemical interaction that occurs between the constituents of cementitious materials (i.e., pore solution, calcium hydroxide, and hydrated cement paste) and salts. Salts were observed to alter the classical phase diagram for a salt-water system which has been conventionally used to interpret the freeze-thaw behavior in concrete. An additional chemical phase change was observed for a concrete-salt-water system resulting in severe damage in cementitious materials. In a cementitioussystem exposed to NaCl, the chemical phase change occurs at a temperature range between -6 °C and 8 °C due to the presence of calcium sulfoaluminate phases in concrete. As a result, concrete exposed to NaCl can experience additional freeze-thaw cycles due to the chemical

Recently, there has been a dramatic increase in premature deterioration in concrete pavements and flat works that are exposed to chloride based salts. Chloride based salts can cause damage and deterioration in concrete due to the combination of factors which include: increased saturation, ice formation, salt crystallization, osmotic pressure, corrosion in steel reinforcement, and/or deleterious chemical reactions. This thesis discusses how chloride based salts interact with cementitious materials to (1) develop damage in concrete, (2) create new chemical phases in concrete, (3) alter transport properties of concrete, and (4) change the concrete freeze-thaw performance. A longitudinal guarded comparative calorimeter (LGCC) was developed to simultaneously measure heat flow, damage development, and phase changes in mortar samples exposed to sodium chloride (NaCl), calcium chloride (CaCl 2), and magnesium chloride (MgCl2) under thermal cycling. Acoustic emission and electrical resistivity measurements were used in conjunction with the LGCC to assess damage development and electrical response of mortar samples during cooling and heating. A low-temperature differential scanning calorimetry (LT-DSC) was used to evaluate the chemical interaction that occurs between the constituents of cementitious materials (i.e., pore solution, calcium hydroxide, and hydrated cement paste) and salts. Salts were observed to alter the classical phase diagram for a salt-water system which has been conventionally used to interpret the freeze-thaw behavior in concrete. An additional chemical phase change was observed for a concrete-salt-water system resulting in severe damage in cementitious materials. In a cementitioussystem exposed to NaCl, the chemical phase change occurs at a temperature range between -6 °C and 8 °C due to the presence of calcium sulfoaluminate phases in concrete. As a result, concrete exposed to NaCl can experience additional freeze-thaw cycles due to the chemical

Effect of nano-sized mineral additions on ductility of engineered cementitious composites (ECC) containing high volumes of fly ash was investigated at different hydration degrees. Various properties of ECC mixtures with different mineral additions were compared in terms of microstructural properties of matrix, fiber-matrix interface, and fiber surface to assess improvements in ductility. Microstructural characterization was made by measuring pore size distributions through mercury intrusion porosimetry (MIP). Hydration characteristics were assessed using thermogravimetric analysis/differential thermal analysis (TGA/DTA), and fiber-matrix interface and fiber surface characteristics were assessed using scanning electron microscopy (SEM) through a period of 90 days. Moreover, compressive and flexural strength developments were monitored for the same period. Test results confirmed that mineral additions could significantly improve both flexural strength and ductility of ECC, especially at early ages. Cheaper Nano-CaCO{sub 3} was more effective compared to nano-silica. However, the crystal structure of CaCO{sub 3} played a very important role in the range of expected improvements.

We investigate the oscillatory reaction dynamics in a closed isothermal chemical system: the reversible Lotka-Volterra model. The second law of thermodynamics dictates that the system ultimately reaches an equilibrium. Quasistationary oscillations are analyzed while the free energy of the system serves as a global Lyapunov function of the dissipative dynamics. A natural distinction between regions near and far from equilibrium in terms of the free energy can be established. The dynamics is analogous to a nonlinear mechanical system with time-dependent increasing damping. Near equilibrium, no oscillation is possible as dictated by Onsager's reciprocal symmetry relation. We observe that while the free energy decreases in the closed system's dynamics, it does not follow the steepest descending path.

Water resources sustainability was estimated using a unique innovative paradigm which parameterized and quantified the relationships between landscape properties and water balance characteristics, by integrating all components of the terrestrial hydrologic system with quantitative watershed characterization. Water is a single resource, regardless of whether it appears as ground or surface water; therefore, in order to address the complex issue of water resources sustainability, it must be characterized together. The key indicator in freshwater sustainability is the ratio of renewable water supply to water use by humans and the environment. At a given point on earth's surface, a combination of different layers, each representing fundamental landscape components, yields unique features related to hydrologic response. Subdividing landscapes into similarly functioning hierarchical structures or hydrologic units (descriptive analysis) at multiple spatial scales enables the quantification of the sustainable water supply. This hydrologic response unit approach can address the sustainability issue because it addresses the fundamentals of the natural spatial and temporal variability of the hydrologic system at a multi-scale organization and long term duration. A statewide analysis of Minnesota was based on the quantification of stream runoff attributes for 129 watersheds (selected from USGS database ) and their association with landscape components defined as the geology (hydrogeology), the stream network system, relief, soils, vegetation and atmosphere (climate ). Multivariate exploratory data analysis techniques were used to establish watershed interconnections based on the spatio-temporal structure of annual, seasonal, monthly and minimal monthly runoff and its linkage to landscape components. Preliminary results identified four main regions with nebulous boundaries with either a positive, negative or absence of trend in annual stream discharge. In each of these regions

The objective of the work described in this report is to demonstrate the capabilities of the current version of LeachXS{trademark}/ORCHESTRA for simulating chemical behavior and constituent release processes in a range of applications that are relevant to the CBP. This report illustrates the use of LeachXS{trademark}/ORCHESTRA for the following applications: (1) Comparing model and experimental results for leaching tests for a range of cementitious materials including cement mortars, grout, stabilized waste, and concrete. The leaching test data includes liquid-solid partitioning as a function of pH and release rates based on laboratory column, monolith, and field testing. (2) Modeling chemical speciation of constituents in cementitious materials, including liquid-solid partitioning and release rates. (3) Evaluating uncertainty in model predictions based on uncertainty in underlying composition, thermodynamic, and transport characteristics. (4) Generating predominance diagrams to evaluate predicted chemical changes as a result of material aging using the example of exposure to atmospheric conditions. (5) Modeling coupled geochemical speciation and diffusion in a three layer system consisting of a layer of Saltstone, a concrete barrier, and a layer of soil in contact with air. The simulations show developing concentration fronts over a time period of 1000 years. (6) Modeling sulfate attack and cracking due to ettringite formation. A detailed example for this case is provided in a separate article by the authors (Sarkar et al. 2010). Finally, based on the computed results, the sensitive input parameters for this type of modeling are identified and discussed. The chemical speciation behavior of substances is calculated for a batch system and also in combination with transport and within a three layer system. This includes release from a barrier to the surrounding soil as a function of time. As input for the simulations, the physical and chemical properties of the

The three-phase system consisting of Nafion, graphite and platinum in the presence of water is studied using molecule dynamics simulation. The force fields describing the molecular interaction between the components in the system are developed to reproduce the energies calculated from density functional theory modeling. The configuration of such complicated three-phase system is predicted through MD simulations. The nanophase-segregation and transport properties are investigated from the equilibrium state. The coverage of the electrolyte on the platinum surface and the dissolution of oxygen are analyzed.

Although the multiscale structure of many important processes in engineering is becoming more widely acknowledged, making this connection in the classroom is a difficult task. This is due in part because the concept of multiscale structure itself is challenging and it requires the students to develop new conceptual pictures of physical systems,…

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations. PMID:17063868

A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin. PMID:21802438

In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow. PMID:23802949

Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process. PMID:26799793

Materials systems have been formulated for the in situ conversion of water-based bentonite drilling fluids into cementitious lost-circulation control materials (CLCM) for use in geothermal wells at temperatures up to 300/sup 0/C. The formulations consist of a cement hardener, a borax admixture, and a fiber glass bridging material which are added to the bentonite fluids. Evaluations of the properties of the slurry and the cured CLCMS revealed that the ions supplied by dissociation of the borax in the CLCM slurry acted to suppress the bentonite hydration and retarded the hardening rate of the cement at elevated temperatures. The CaO-SiO/sub 2/-H/sub 2/O (C-S-H) phases formed during curing of the CLCM play essential roles in improving the quality of the hardened CLCMs. It was observed that xonotlite-truscottite transformation resulted in strength reductions and increased water permeability. The plugging ability of fiber glass depends on the conentration and fiber size. The silicate ions dissolved by hot alkaline disintegration of the fiber glass were chemisorbed with Ca/sup 2 +/ ions from the cement and led to the precipitation of C-S-H compounds on the fiber surfaces, which improved bond strength at the matrix-fiber interfaces.

Research commenced in FY 97 to determine the suitability of superplasticized cement-sand grouts for backfilling vertical boreholes used with geothermal heat pump (GHP) systems. The overall objectives were to develop, evaluate and demonstrate cementitious grouts that could reduce the required bore length and improve the performance of GHPs. This report summarizes the accomplishments in FY 98. The developed thermally conductive grout consists of cement, water, a particular grade of silica sand, superplasticizer and a small amount of bentonite. While the primary function of the grout is to facilitate heat transfer between the U-loop and surrounding formation, it is also essential that the grout act as an effective borehole sealant. Two types of permeability (hydraulic conductivity) tests was conducted to evaluate the sealing performance of the cement-sand grout. Additional properties of the proposed grout that were investigated include bleeding, shrinkage, bond strength, freeze-thaw durability, compressive, flexural and tensile strengths, elastic modulus, Poisson`s ratio and ultrasonic pulse velocity.

High performance concrete prepared from general purpose (GP) portland cement and various supplementary cementitious materials are increasingly finding their use in construction worldwide. This study was undertaken to compare mechanical properties as well as fresh concrete properties of concretes containing silica fume, ground granulated blast furnace slag (slag), fly ash and GP portland cement. The aim of the study was to enable evaluation of the suitability of a particular binder system for an application based on fresh concrete properties and mechanical properties. Concrete mixes were prepared with GP portland cement, high slag cement and slag cement, and also mixes were prepared with the addition of silica fume and fly ash. The work focused on concrete mixes having a fixed water/binder ratio of 0.35 and a constant total binder content of 430 kg/m[sup 3]. Apart from measuring fresh concrete properties, the mechanical properties evaluated were development of compressive strength, flexural strength, elastic modulus, and strain due to creep and drying shrinkage. Results indicated that the addition of silica fume to GP portland cement concrete marginally decreased the workability of the concrete but significantly improved the mechanical properties. However, the effect of addition of silica fume to high slag cement concrete was less pronounced.

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models. PMID:26885640

Cementitious materials are conventionally used in conditioning intermediate and low level radioactive waste. In this study a candidate cement-based wasteform has been investigated using neutron imaging to characterise the wasteform for disposal in a repository for radioactive materials. Imaging showed both the pore size distribution and the extent of the cracking that had occurred in the samples. The rate of the water penetration measured both by conventional sorptivity measurements and neutron imaging was greater than in pastes made from Ordinary Portland Cement. The ability of the cracks to distribute the water through the sample in a very short time was also evident. The study highlights the significant potential of neutron imaging in the investigation of cementitious materials. The technique has the advantage of visualising and measuring, non-destructively, material distribution within macroscopic samples and is particularly useful in defining movement of water through the cementitious materials.

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

The Cementitious Barriers Partnership (CBP) was created to develop predictive capabilities for the aging of cementitious barriers over long timeframes. The CBP is a multi-agency, multi-national consortium working under a U.S. Department of Energy (DOE) Environmental Management (EM-21) funded Cooperative Research and Development Agreement (CRADA) with the Savannah River National Laboratory (SRNL) as the lead laboratory. Members of the CBP are SRNL, Vanderbilt University, the U.S. Nuclear Regulatory Commission (USNRC), National Institute of Standards and Technology (NIST), SIMCO Technologies, Inc. (Canada), and the Energy Research Centre of the Netherlands (ECN). A first step in developing advanced tools is to determine the current state-of-the-art. A review has been undertaken to assess the treatment of cementitious barriers in Performance Assessments (PA). Representatives of US DOE sites which have PAs for their low level waste disposal facilities were contacted. These sites are the Idaho National Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, Nevada Test Site, and Hanford. Several of the more arid sites did not employ cementitious barriers. Of those sites which do employ cementitious barriers, a wide range of treatment of the barriers in a PA was present. Some sites used conservative, simplistic models that even though conservative still showed compliance with disposal limits. Other sites used much more detailed models to demonstrate compliance. These more detailed models tend to be correlation-based rather than mechanistically-based. With the US DOE's Low Level Waste Disposal Federal Review Group (LFRG) moving towards embracing a risk-based, best estimate with an uncertainties type of analysis, the conservative treatment of the cementitious barriers seems to be obviated. The CBP is creating a tool that adheres to the LFRG chairman's paradigm of continuous improvement.

HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic

Ohmic RF-MEMS switches hold much promise for low power wireless communication, but long-term degradation currently plagues their reliable use. Failure in these devices occurs at the contact and is complicated by the fact that the same asperities that bear the mechanical load are also important to the flow of electrical current needed for signal processing. Materials selection holds the key to overcoming the barriers that prevent widespread use. Current efforts in materials selection have been based on the material's (or alloy's) ability to resist oxidation as well as its room-temperature properties, such as hardness and electrical conductivity. No ideal solution has yet been found via this route. This may be due, in part, to the fact that the in-use changes to the local environment of the asperity are not included in the selection criteria. For example, Joule heating would be expected to raise the local temperature of the asperity and impose a non-equilibrium thermal gradient in the same region expected to respond to mechanical actuation. We propose that these conditions should be considered in the selection process, as they would be expected to alter mechanical, electrical, and chemical mechanisms in the vicinity of the surface. To this end, we simulate the actuation of an Ohmic radio frequency micro electro mechanical systems switch by using a multi-scale method to model a current-carrying asperity in contact with a polycrystalline substrate. Our method couples continuum solutions of electrical and thermal transport equations to an underlying molecular dynamics simulation. We present simulations of gold-nickel asperities and substrates in order to evaluate the influence of alloying and local order on the early stages of contact actuation. The room temperature response of these materials is compared to the response of the material when a voltage is applied. Au-Ni interactions are accounted for through modification of the existing Zhou embedded atom method

HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic

We compute and compare the three types of vectors frequently used to explore the instability properties of dynamical models, namely Lyapunov vectors (LVs), singular vectors (SVs) and bred vectors (BVs) in two systems, using the Wolfe-Samelson (2007 Tellus A 59 355-66) algorithm to compute all of the Lyapunov vectors. The first system is the Lorenz (1963 J. Atmos. Sci. 20 130-41) three-variable model. Although the leading Lyapunov vector, LV1, grows fastest globally, the second Lyapunov vector, LV2, which has zero growth globally, often grows faster than LV1 locally. Whenever this happens, BVs grow closer to LV2, suggesting that in larger atmospheric or oceanic models where several instabilities can grow in different areas of the world, BVs will grow toward the fastest growing local unstable mode. A comparison of their growth rates at different times shows that all three types of dynamical vectors have the ability to predict regime changes and the duration of the new regime based on their growth rates in the last orbit of the old regime, as shown for BVs by Evans et al (2004 Bull. Am. Meteorol. Soc. 520-4). LV1 and BVs have similar predictive skill, LV2 has a tendency to produce false alarms, and even LV3 shows that maximum decay is also associated with regime change. Initial and final SVs grow much faster and are the most accurate predictors of regime change, although the characteristics of the initial SVs are strongly dependent on the length of the optimization window. The second system is the toy ‘ocean-atmosphere’ model developed by Peña and Kalnay (2004 Nonlinear Process. Geophys. 11 319-27) coupling three Lorenz (1963 J. Atmos. Sci. 20 130-41) systems with different time scales, in order to test the effects of fast and slow modes of growth on the dynamical vectors. A fast ‘extratropical atmosphere’ is weakly coupled to a fast ‘tropical atmosphere’ which is, in turn, strongly coupled to a slow ‘ocean’ system, the latter coupling imitating the

This study aims to improve land surface processes in a retrospective meteorology and air quality modeling system through the use of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation and albedo products for more realistic vegetation and surface representation. MODIS leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and albedo are incorporated into the Pleim-Xiu land surface model (PX LSM) used in a combined meteorology and air quality modeling system. The current PX LSM intentionally exaggerates vegetation coverage and LAI in western dry lands so that its soil moisture nudging scheme is more effective in simulating surface temperature and mixing ratio. Reduced vegetation coverage from the PX LSM with MODIS input results in hotter and dryer daytime conditions with reduced ozone dry deposition velocities in much of western North America. Evaluations of the new system indicate greater error and bias in temperature, but reduced error and bias in moisture with the MODIS vegetation input. Hotter daytime temperatures and reduced dry deposition result in greater ozone concentrations in the western arid regions even with deeper boundary layer depths. MODIS albedo has much less impact on the meteorology simulations than MODIS LAI and FPAR. The MODIS vegetation and albedo input does not have much influence in the east where differences in vegetation and albedo parameters are less extreme. Evaluation results showing increased temperature errors with more accurate representation of vegetation suggests that improvements are needed in the model surface physics, particularly the soil processes in the PX LSM.

A cementitious composition comprising a cementitious material and polyethylene glycol or end-capped polyethylene glycol as a phase change material, said polyethylene glycol and said end-capped polyethylene glycol having a molecular weight greater than about 400 and a heat of fusion greater than about 30 cal/g; the compositions are useful in making pre-formed building materials such as concrete blocks, brick, dry wall and the like or in making poured structures such as walls or floor pads; the glycols can be encapsulated to reduce their tendency to retard set.

Modulus of elasticity is a vital property in cementitious material (CM) design and analysis. A better understanding of the relationship between density, strength and stiffness is needed to construct proper structures especially with reinforced cementitious materials. For this purpose, modulus of elasticity of CMs with different waste aggregates was analyzed and the reliability of estimated values of various equations proposed by standards and sources in literature, suggested in this investigation and derived by a software chosen was discussed. The results demonstrated that as compared to experimental results, the model developed by software was the most accurate as the percentages of error in prediction were in a good agreement.

Disclosed are methods for determining the redox condition of cementitious materials. The methods are leaching methods that utilize a redox active transition metal indicator that is present in the cementitious material and exhibits variable solubility depending upon the oxidation state of the indicator. When the leaching process is carried out under anaerobic conditions, the presence or absence of the indicator in the leachate can be utilized to determine the redox condition of and location of the oxidation front in the material that has been subjected to the leaching process.

Robotic mapping and localization systems typically operate at either one fixed spatial scale, or over two, combining a local metric map and a global topological map. In contrast, recent high profile discoveries in neuroscience have indicated that animals such as rodents navigate the world using multiple parallel maps, with each map encoding the world at a specific spatial scale. While a number of theoretical-only investigations have hypothesized several possible benefits of such a multi-scale mapping system, no one has comprehensively investigated the potential mapping and place recognition performance benefits for navigating robots in large real world environments, especially using more than two homogeneous map scales. In this paper we present a biologically-inspired multi-scale mapping system mimicking the rodent multi-scale map. Unlike hybrid metric-topological multi-scale robot mapping systems, this new system is homogeneous, distinguishable only by scale, like rodent neural maps. We present methods for training each network to learn and recognize places at a specific spatial scale, and techniques for combining the output from each of these parallel networks. This approach differs from traditional probabilistic robotic methods, where place recognition spatial specificity is passively driven by models of sensor uncertainty. Instead we intentionally create parallel learning systems that learn associations between sensory input and the environment at different spatial scales. We also conduct a systematic series of experiments and parameter studies that determine the effect on performance of using different neural map scaling ratios and different numbers of discrete map scales. The results demonstrate that a multi-scale approach universally improves place recognition performance and is capable of producing better than state of the art performance compared to existing robotic navigation algorithms. We analyze the results and discuss the implications with respect to

A cementitious waste form, Cast Stone, is being evaluated as a possible supplemental immobilization technology for the Hanford sites's low activity waste (LAW), which contains radioactive 99Tc and 129I, as part of the tank waste cleanup mission. Cast Stone is made of a dry blend 47% blast furnace slag, 45% fly ash, and 8% ordinary Portland cement, mixed with a low-activity waste (LAW). To improve the retention of Tc and/or I in Cast Stone, materials with a high affinity for Tc and/or I, termed "getters," can be added to provide a stable domain for the radionuclides of concern. Previous testing conducted with a variety of getters has identified Tin(II)-Apatite and Silver Exchanged Zeolite as promising candidates for Tc and I, respectively. Investigation into the sequence in which getters are added to Cast Stone was performed following two methods: 1) adding getters to the Cast Stone dry blend, and then mixing with liquid waste, and 2) adding getters to the liquid waste first, followed by addition of the Cast Stone dry blend. Cast Stone monolith samples were prepared with each method and leach tests, following EPA method 1315, were conducted in either distilled water or simulated vadose zone porewater for a period of up to 63 days. The leachate was analyzed for Tc, I, Na, NO3-, NO2- and Cr with ICP-MS, ICP-OES and ion chromatography and the results indicated that the Cast Stone with getter addition in the dry blend mix (method 1) has lower rates of Tc and I leaching. The mechanisms of radionuclide release from the Cast Stone were also investigated with a variety of solid phase characterization techniques of the monoliths before and after leaching, such as XRD, SEM/EDS, TEM/SAED and other spectroscopic techniques.

The pyroclastic aggregate concrete of Trajan’s Markets (110 CE), now Museo Fori Imperiali in Rome, has absorbed energy from seismic ground shaking and long-term foundation settlement for nearly two millenia while remaining largely intact at the structural scale. The scientific basis of this exceptional service record is explored through computed tomography of fracture surfaces and synchroton X-ray microdiffraction analyses of a reproduction of the standardized hydrated lime–volcanic ash mortar that binds decimeter-sized tuff and brick aggregate in the conglomeratic concrete. The mortar reproduction gains fracture toughness over 180 d through progressive coalescence of calcium–aluminum-silicate–hydrate (C-A-S-H) cementing binder with Ca/(Si+Al) ≈more » 0.8–0.9 and crystallization of strätlingite and siliceous hydrogarnet (katoite) at ≥90 d, after pozzolanic consumption of hydrated lime was complete. Platey strätlingite crystals toughen interfacial zones along scoria perimeters and impede macroscale propagation of crack segments. In the 1,900 year old mortar, C-A-S-H has low Ca/(Si+Al) ≈ 0.45–0.75. Dense clusters of 2- to 30-µm strätlingite plates further reinforce interfacial zones, the weakest link of modern cement-based concrete, and the cementitious matrix. These crystals formed during long-term autogeneous reaction of dissolved calcite from lime and the alkali-rich scoriae groundmass, clay mineral (halloysite), and zeolite (phillipsite and chabazite) surface textures from the Pozzolane Rosse pyroclastic flow, erupted from the nearby Alban Hills volcano. The clast-supported conglomeratic fabric of the concrete presents further resistance to fracture propagation at the structural scale.« less

Digesters produce biogas from organic wastes through anaerobic digestion processes. These digesters, often made of concrete, suffer severe premature deterioration caused mainly by the presence of fermentative microorganisms producing metabolites that are aggressive towards cementitious materials. To clarify the degradation mechanisms in an anaerobic digestion medium, ordinary Portland cement paste specimens were immersed in the liquid fraction of a running, lab-scale digester for 4weeks. The anaerobic digestion medium was a mixture of a biowaste substrate and sludge from municipal wastewater treatment plant used as a source of anaerobic bacteria. The chemical characteristics of the anaerobic digestion liquid phase were monitored over time using a pH metre, high performance liquid chromatography (HPLC) and ion chromatography (HPIC). An initial critical period of low pH in the bioreactors was observed before the pH stabilized around 8. Acetic, propionic and butyric acids were produced during the digestion with a maximum total organic acid concentration of 50mmolL(-1). The maximum ammonium content of the liquid phase was 40mmolL(-1), which was about seven times the upper limit of the highly aggressive chemical environment class (XA3) as defined by the European standard for the specification of concrete design in chemically aggressive environments (EN 206). The changes in the mineralogical, microstructural and chemical characteristics of the cement pastes exposed to the solid and liquid phase of the digesters were analysed at the end of the immersion period by X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectrometry (EDS) and electron-probe micro-analysis (EPMA). A 700-μm thick altered layer was identified in the cement paste specimens. The main biodeterioration patterns in the bioreactors' solid/liquid phase were calcium leaching and carbonation of the cement matrix. PMID:27432729

Concrete, when designed and constructed properly, is a durable material. However in aggressive environments concrete is prone to gradual deterioration which is due to penetration of water and aggressive agents (e.g., chloride ions) into concrete. As such, the rate of mass transport is the primary factor, controlling the durability of cementitious materials. Some level of cracking is inevitable in concrete due to brittle nature of the material. While mass transport can occur through concrete’s porous matrix, cracks can significantly accelerate the rate of mass transport and effectively influence the service life of concrete structures. To allow concrete service life prediction models to correctly account for the effect of cracks on concrete durability, mass transport thru cracks must be characterized. In this study, transport properties of cracks are measured to quantify the saturated hydraulic permeability and diffusion coefficient of cracks as a function of crack geometry (i.e.; crack width, crack tortuosity and crack wall roughness). Saturated permeability and diffusion coefficient of cracks are measured by constant head permeability test, electrical migration test, and electrical impedance spectroscopy. Plain and fiber reinforced cement paste and mortar as well as simulated crack samples are tested. The results of permeability test showed that the permeability of a crack is a function of crack width squared and can be predicted using Louis formula when crack tortuosity and surface roughness of the crack walls are accounted for. The results of the migration and impedance tests showed that the diffusion coefficient of the crack is not dependent on the crack width, but is primarily a function of volume fraction of cracks. The only parameter that is changing with the crack width is the crack connectivity. Crack connectivity was found to be linearly dependent on crack width for small crack and constant for large cracks (i.e.; approximately larger than 80 µm). The

The pyroclastic aggregate concrete of Trajan's Markets (110 CE), now Museo Fori Imperiali in Rome, has absorbed energy from seismic ground shaking and long-term foundation settlement for nearly two millenia while remaining largely intact at the structural scale. The scientific basis of this exceptional service record is explored through computed tomography of fracture surfaces and synchroton X-ray microdiffraction analyses of a reproduction of the standardized hydrated lime-volcanic ash mortar that binds decimeter-sized tuff and brick aggregate in the conglomeratic concrete. The mortar reproduction gains fracture toughness over 180 d through progressive coalescence of calcium-aluminum-silicate-hydrate (C-A-S-H) cementing binder with Ca/(Si+Al) ≈ 0.8-0.9 and crystallization of strätlingite and siliceous hydrogarnet (katoite) at ≥ 90 d, after pozzolanic consumption of hydrated lime was complete. Platey strätlingite crystals toughen interfacial zones along scoria perimeters and impede macroscale propagation of crack segments. In the 1,900-y-old mortar, C-A-S-H has low Ca/(Si+Al) ≈ 0.45-0.75. Dense clusters of 2- to 30-µm strätlingite plates further reinforce interfacial zones, the weakest link of modern cement-based concrete, and the cementitious matrix. These crystals formed during long-term autogeneous reaction of dissolved calcite from lime and the alkali-rich scoriae groundmass, clay mineral (halloysite), and zeolite (phillipsite and chabazite) surface textures from the Pozzolane Rosse pyroclastic flow, erupted from the nearby Alban Hills volcano. The clast-supported conglomeratic fabric of the concrete presents further resistance to fracture propagation at the structural scale. PMID:25512521

The pyroclastic aggregate concrete of Trajan’s Markets (110 CE), now Museo Fori Imperiali in Rome, has absorbed energy from seismic ground shaking and long-term foundation settlement for nearly two millenia while remaining largely intact at the structural scale. The scientific basis of this exceptional service record is explored through computed tomography of fracture surfaces and synchroton X-ray microdiffraction analyses of a reproduction of the standardized hydrated lime–volcanic ash mortar that binds decimeter-sized tuff and brick aggregate in the conglomeratic concrete. The mortar reproduction gains fracture toughness over 180 d through progressive coalescence of calcium–aluminum-silicate–hydrate (C-A-S-H) cementing binder with Ca/(Si+Al) ≈ 0.8–0.9 and crystallization of strätlingite and siliceous hydrogarnet (katoite) at ≥90 d, after pozzolanic consumption of hydrated lime was complete. Platey strätlingite crystals toughen interfacial zones along scoria perimeters and impede macroscale propagation of crack segments. In the 1,900 year old mortar, C-A-S-H has low Ca/(Si+Al) ≈ 0.45–0.75. Dense clusters of 2- to 30-µm strätlingite plates further reinforce interfacial zones, the weakest link of modern cement-based concrete, and the cementitious matrix. These crystals formed during long-term autogeneous reaction of dissolved calcite from lime and the alkali-rich scoriae groundmass, clay mineral (halloysite), and zeolite (phillipsite and chabazite) surface textures from the Pozzolane Rosse pyroclastic flow, erupted from the nearby Alban Hills volcano. The clast-supported conglomeratic fabric of the concrete presents further resistance to fracture propagation at the structural scale.

Axial loads on plugs or seals in an underground repository due to gas, water pressures and temperature changes induced subsequent to waste and plug emplacement lead to shear stresses at the plug/rock contact. Therefore, the bond between the plug and rock is a critical element for the design and effectiveness of plugs in boreholes, shafts or tunnels. This study includes a systematic investigation of the bond strength of cementitious borehole plugs in welded tuff. Analytical and numerical analysis of borehole plug-rock stress transfer mechanics is performed. The interface strength and deformation are studied as a function of Young`s modulus ratio of plug and rock, plug length and rock cylinder outside-to-inside radius ratio. The tensile stresses in and near an axially loaded plug are analyzed. The frictional interface strength of an axially loaded borehole plug, the effect of axial stress and lateral external stress, and thermal effects are also analyzed. Implications for plug design are discussed. The main conclusion is a strong recommendation to design friction plugs in shafts, drifts, tunnels or boreholes with a minimum length to diameter ratio of four. Such a geometrical design will reduce tensile stresses in the plug and in the host rock to a level which should minimize the risk of long-term deterioration caused by excessive tensile stresses. Push-out tests have been used to determine the bond strength by applying an axial load to cement plugs emplaced in boreholes in welded tuff cylinders. A total of 130 push-out tests have been performed as a function of borehole size, plug length, temperature, and degree of saturation of the host tuff. The use of four different borehole radii enables evaluation of size effects. 119 refs., 42 figs., 20 tabs.

The pyroclastic aggregate concrete of Trajan’s Markets (110 CE), now Museo Fori Imperiali in Rome, has absorbed energy from seismic ground shaking and long-term foundation settlement for nearly two millenia while remaining largely intact at the structural scale. The scientific basis of this exceptional service record is explored through computed tomography of fracture surfaces and synchroton X-ray microdiffraction analyses of a reproduction of the standardized hydrated lime–volcanic ash mortar that binds decimeter-sized tuff and brick aggregate in the conglomeratic concrete. The mortar reproduction gains fracture toughness over 180 d through progressive coalescence of calcium–aluminum-silicate–hydrate (C-A-S-H) cementing binder with Ca/(Si+Al) ≈ 0.8–0.9 and crystallization of strätlingite and siliceous hydrogarnet (katoite) at ≥90 d, after pozzolanic consumption of hydrated lime was complete. Platey strätlingite crystals toughen interfacial zones along scoria perimeters and impede macroscale propagation of crack segments. In the 1,900-y-old mortar, C-A-S-H has low Ca/(Si+Al) ≈ 0.45–0.75. Dense clusters of 2- to 30-µm strätlingite plates further reinforce interfacial zones, the weakest link of modern cement-based concrete, and the cementitious matrix. These crystals formed during long-term autogeneous reaction of dissolved calcite from lime and the alkali-rich scoriae groundmass, clay mineral (halloysite), and zeolite (phillipsite and chabazite) surface textures from the Pozzolane Rosse pyroclastic flow, erupted from the nearby Alban Hills volcano. The clast-supported conglomeratic fabric of the concrete presents further resistance to fracture propagation at the structural scale. PMID:25512521

The properties of concretes containing various waste E-glass particle contents were investigated in this study. Waste E-glass particles were obtained from electronic grade glass yarn scrap by grinding to small particle size. The size distribution of cylindrical glass particle was from 38 to 300 {mu}m and about 40% of E-glass particle was less than 150 {mu}m. The E-glass mainly consists of SiO{sub 2}, Al{sub 2}O{sub 3}, Ca O and MgO, and is indicated as amorphous by X-ray diffraction (XRD) technique. Compressive strength and resistance of sulfate attack and chloride ion penetration were significantly improved by utilizing proper amount of waste E-glass in concrete. The compressive strength of specimen with 40 wt.% E-glass content was 17%, 27% and 43% higher than that of control specimen at age of 28, 91 and 365 days, respectively. E-glass can be used in concrete as cementitious material as well as inert filler, which depending upon the particle size, and the dividing size appears to be 75 {mu}m. The workability decreased as the glass content increased due to reduction of fineness modulus, and the addition of high-range water reducers was needed to obtain a uniform mix. Little difference was observed in ASR testing results between control and E-glass specimens. Based on the properties of hardened concrete, optimum E-glass content was found to be 40-50 wt.%.

The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomass transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.

The US DOE has initiated a multidisciplinary cross cutting project to develop a reasonable and credible set of tools to predict the structural, hydraulic and chemical performance of cement barriers used in nuclear applications over extended time frames (e.g., > 100 years for operating facilities and > 1000 years for waste management). A partnership that combines DOE, NRC, academia, private sector, and international expertise has been formed to accomplish the project objectives by integrating existing information and realizing advancements where necessary. The set of simulation tools and data developed under this project will be used to evaluate and predict the behavior of cementitious barriers used in near surface engineered waste disposal systems, e.g., waste forms, containment structures, entombments and environmental remediation, including decontamination and decommissioning (D&D) activities. The simulation tools will also support analysis of structural concrete components of nuclear facilities (spent fuel pools, dry spent fuel storage units, and recycling facilities, e.g., fuel fabrication, separations processes). Simulation parameters will be obtained from prior literature and will be experimentally measured under this project, as necessary, to demonstrate application of the simulation tools for three prototype applications (waste form in concrete vault, high level waste tank grouting, and spent fuel pool). Test methods and data needs to support use of the simulation tools for future applications will be defined. This is a national issue that affects all waste disposal sites that use cementitious waste forms and structures, decontamination and decommissioning activities, service life determination of existing structures, and design of future public and private nuclear facilities. The problem is difficult because it requires projecting conditions and responses over extremely long times. Current performance assessment analyses show that engineered barriers are

In Switzerland, deep geological storage in clay rich host rocks is the preferred option for low- and intermediate-level radioactive waste. For these waste types cementitious materials are used for tunnel support and backfill, waste containers and waste matrixes. The different geochemical characteristics of clay and cementitious materials may induce mineralogical and pore water changes which might affect the barrier functionality of host rocks and concretes. We present numerical reactive transport calculations that systematically compare the geochemical evolution at cement/clay interfaces for the proposed host rocks in Switzerland for different transport scenarios. We developed a consistent set of thermodynamic data, simultaneously valid for cementitious (concrete) and clay materials. With our setup we successfully reproduced mineralogies, water contents and pore water compositions of the proposed host rocks and of a reference concrete. Our calculations show that the effects of geochemical gradients between concrete and clay materials are very similar for all investigated host rocks. The mineralogical changes at material interfaces are restricted to narrow zones for all host rocks. The extent of strong pH increase in the host rocks is limited, although a slight increase of pH over greater distances seems possible in advective transport scenarios. Our diffusive and partially also the advective calculations show massive porosity changes due to precipitation/dissolution of mineral phases near the interface, in line with many other reported transport calculations on cement/clay interactions. For all investigated transport scenarios the degradation of concrete materials in emplacement caverns due to diffusive and advective transport of clay pore water into the caverns is limited to narrow zones. A specific effort has been made to improve the geochemical setup and the extensive use of solid solution phases demonstrated the successful application of a thermodynamically

Annually, tens of millions of first-ever strokes occur in the world; however, currently there is lack of effective and widely applicable pharmacological treatments for stroke patients. Herbal medicines, characterized as multi-constituent, multi-target and multi-effect, have been acknowledged with conspicuous effects in treating stroke, and attract extensive interest of researchers although the mechanism of action is yet unclear. In this work, we introduce an innovative systems-pharmacology method that combines pharmacokinetic prescreening, target fishing and network analysis to decipher the mechanisms of action of 10 herbal medicines like Salvia miltiorrhizae, Ginkgo biloba and Ephedrae herba which are efficient in stroke treatment and prevention. Our systematic analysis results display that, in these anti-stroke herbal medicines, 168 out of 1285 constituents with the favorable pharmacokinetic profiles might be implicated in stroke therapy, and the systematic use of these compounds probably acts through multiple mechanisms to synergistically benefit patients with stroke, which can roughly be classified as preventing ischemic inflammatory response, scavenging free radicals and inhibiting neuronal apoptosis against ischemic cerebral damage, as well as exhibiting lipid-lowering, anti-diabetic, anti-thrombotic and antiplatelet effects to decrease recurrent strokes. Relying on systems biology-based analysis, we speculate that herbal medicines, being characterized as the classical combination therapies, might be not only engaged in multiple mechanisms of action to synergistically improve the stroke outcomes, but also might be participated in reducing the risk factors for recurrent strokes. PMID:25093322

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

The MM5-SMOKE-CMAQ model system, which is developed by the United States Environmental Protection Agency(U.S. EPA) as the Models-3 system, has been used for the daily air quality forecast in the Beijing Municipal Environmental Monitoring Center(Beijing MEMC), as a part of the Ensemble Air Quality Forecast System for Beijing(EMS-Beijing) since the Olympic Games year 2008. In this study, we collect the daily forecast results of the CMAQ model in the whole year 2010 for the model evaluation. The results show that the model play a good model performance in most days but underestimate obviously in some air pollution episode. A typical air pollution episode from 11st - 20th January 2010 was chosen, which the air pollution index(API) of particulate matter (PM10) observed by Beijing MEMC reaches to 180 while the prediction of PM10-API is about 100. Taking in account all stations in Beijing, including urban and suburban stations, three numerical methods are used for model improvement: firstly, enhance the inner domain with 4km grids, the coverage from only Beijing to the area including its surrounding cities; secondly, update the Beijing stationary area emission inventory, from statistical county-level to village-town level, that would provide more detail spatial informance for area emissions; thirdly, add some industrial points emission in Beijing's surrounding cities, the latter two are both the improvement of emission. As the result, the peak of the nine national standard stations averaged PM10-API, which is simulated by CMAQ as daily hindcast PM10-API, reach to 160 and much near to the observation. The new results show better model performance, which the correlation coefficent is 0.93 in national standard stations average and 0.84 in all stations, the relative error is 15.7% in national standard stations averaged and 27% in all stations. The time series of 9 national standard in Beijing urban The scatter diagram of all stations in Beijing, the red is the forecast and

The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El

Present and future tropospheric ozone (O3) concentrations over east Asia have been simulated by the Models-3 Community Multiscale Air Quality Modeling System (CMAQ) coupled with the Regional Emission Inventory in Asia (REAS) to predict surface O3 variations caused by future anthropogenic emissions changes. For future prediction, REAS provides three emission scenarios for China (the reference (REF), the policy succeed case (PSC), and the policy failure case (PFC) scenarios) and one emission scenario (the REF scenario) for the other countries. Simulated O3 concentration in summer was relatively high (70-80 ppbv in June and 65-75 ppbv in August) over the North China Plain in 2000. The projected REF emissions for 2020 (2020REF) enhance the monthly averaged O3 to 75-90 ppbv in June and 75-85 ppbv in August. The projected PSC emissions for 2020 (2020PFC), including a slight NOx reduction of -0.2 Tg (-2%) and a large NMVOC increase of 14.3 Tg (97%) for total Chinese emissions during 2000-2020, cause the monthly and annually averaged O3 concentrations to decrease by less than 2 ppbv in northeastern and central China. Over the North China Plain, the projected PFC emissions for 2020 (2020PFC) cause significant increases, more than 20 ppbv in the monthly averaged O3, and the O3 will be 85-105 ppbv in June and 80-95 ppbv in August for 2020. The 2020PFC also affect O3 increases in early summer in South Korea (14-18 ppbv increase for monthly average) and Japan (2-14 ppbv increase for monthly average) during 2000-2020 despite the slight NOx increase of 0.4 Tg (25%) in South Korea and the slight NOx reduction of -0.2 Tg (-10%) in Japan during 2000-2020. The pollutant in these regions seems to be transport from upwind source regions. These experiments show that over central eastern China at midday in June, the O3 concentration is largely affected by NOx emission increases but is insensitive to NMVOC emission increases.

A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

The recently introduced multiscale entropy (MSE) method accounts for long range correlations over multiple time scales and can therefore reveal the complexity of biological signals. The existing MSE algorithm deals with scalar time series whereas multivariate time series are common in experimental and biological systems. To that cause, in this paper the MSE method is extended to the multivariate case. This allows us to gain a greater insight into the complexity of the underlying signal generating system, producing multifaceted and more robust estimates than standard single channel MSE. Simulations on both synthetic data and brain consciousness analysis support the approach. PMID:22254434

Several dairy farms in the Netherlands aim at reducing environmental impacts by improving the internal nutrient cycle (INC) on their farm by optimizing the use of available on-farm resources. This study evaluates the environmental performance of selected INC farms in the Northern Friesian Woodlands in comparison to regular benchmark farms using a Life Cycle Assessment. Regular farms were selected on the basis of comparability in terms of milk production per farm and per hectare, soil type and drainage conditions. In addition, the environmental impacts of INC farming at landscape level were evaluated with the integrated modelling system INITIATOR, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil, assuming that all farms practised the principle of INC farming. Impact categories used at both farm and landscape levels were global warming potential, acidification potential and eutrophication potential. Additional farm level indicators were land occupation and non-renewable energy use, and furthermore all farm level indicators were also expressed per kg fat and protein corrected milk. Results showed that both on-farm and off-farm non-renewable energy use was significantly lower at INC farms as compared with regular farms. Although nearly all other environmental impacts were numerically lower, both on-farm and off-farm, differences were not statistically significant. Nitrogen losses to air and water decreased by on average 5 to 10% when INC farming would be implemented for the whole region. The impact of INC farming on the global warming potential and eutrophication potential was, however, almost negligible (<2%) at regional level. This was due to a negligible impact on the methane emissions and on the surplus and thereby on the soil accumulation and losses of phosphorus to water at INC farms, illustrating the focus of these farms on closing the nitrogen cycle. PMID:26231773

In vivo high-resolution imaging of tumor development is possible through dorsal skinfold chamber implantable on mice model. However, current intravital imaging systems are weakly tolerated along time by mice and do not allow multimodality imaging. Our project aims to develop a new chamber for: 1- long-term micro/macroscopic visualization of tumor (vascular and cellular compartments) and tissue microenvironment; and 2- multimodality imaging (photonic, MRI and sonography). Our new experimental device was patented in March 2014 and was primarily assessed on 75 mouse engrafted with 4T1-Luc tumor cell line, and validated in confocal and multiphoton imaging after staining the mice vasculature using Dextran 155KDa-TRITC or Dextran 2000kDa-FITC. Simultaneously, a universal stage was designed for optimal removal of respiratory and cardiac artifacts during microscopy assays. Experimental results from optical, ultrasound (Bmode and pulse subtraction mode) and MRI imaging (anatomic sequences) showed that our patented design, unlike commercial devices, improves longitudinal monitoring over several weeks (35 days on average against 12 for the commercial chamber) and allows for a better characterization of the early and late tissue alterations due to tumour development. We also demonstrated the compatibility for multimodality imaging and the increase of mice survival was by a factor of 2.9, with our new skinfold chamber. Current developments include: 1- defining new procedures for multi-labelling of cells and tissue (screening of fluorescent molecules and imaging protocols); 2- developing ultrasound and MRI imaging procedures with specific probes; 3- correlating optical/ultrasound/MRI data for a complete mapping of tumour development and microenvironment.

We develop and apply a full waveform inversion method that incorporates seismic data on a wide range of spatio-temporal scales, thereby constraining the details of both crustal and upper-mantle structure. This is intended to further our understanding of crust-mantle interactions that shape the nature of plate tectonics, and to be a step towards improved tomographic models of strongly scale-dependent earth properties, such as attenuation and anisotropy. The inversion for detailed regional earth structure consistently embedded within a large-scale model requires locally refined numerical meshes that allow us to (1) model regional wave propagation at high frequencies, and (2) capture the inferred fine-scale heterogeneities. The smallest local grid spacing sets the upper bound of the largest possible time step used to iteratively advance the seismic wave field. This limitation leads to extreme computational costs in the presence of fine-scale structure, and it inhibits the construction of full waveform tomographic models that describe earth structure on multiple scales. To reduce computational requirements to a feasible level, we design a multigrid approach based on the decomposition of a multiscale earth model with widely varying grid spacings into a family of single-scale models where the grid spacing is approximately uniform. Each of the single-scale models contains a tractable number of grid points, which ensures computational efficiency. The multi-to-single-scale decomposition is the foundation of iterative, gradient-based optimization schemes that simultaneously and consistently invert data on all scales for one multi-scale model. We demonstrate the applicability of our method in a full waveform inversion for Eurasia, with a special focus on Anatolia where coverage is particularly dense. Continental-scale structure is constrained by complete seismic waveforms in the 30-200 s period range. In addition to the well-known structural elements of the Eurasian mantle

The lung is geometrically articulated across multiple scales from the trachea to the alveoli. A major computational challenge is to tightly link ODEs that describe lower scales to 3D finite element or finite volume models of airway mechanics using iterative communication between scales. In this study, we developed a novel multiscale computational framework for bidirectionally coupling 3D CFD models and systems of lower order ODEs. To validate the coupling framework, a four and eight generation Weibel lung model was constructed. For the coupled CFD-ODE simulations, the lung models were truncated at different generations and a RL circuit represented the truncated portion. The flow characteristics from the coupled models were compared to untruncated full 3D CFD models at peak inhalation and peak exhalation. Results showed that at no time or simulation was the difference in mass flux and/or pressure at a given location between uncoupled and coupled models was greater than 2.43%. The flow characteristics at prime locations for the coupled models showed good agreement to uncoupled models. Remarkably, due to reuse of the Krylov subspace, the cost of the ODE coupling is not much greater than uncoupled full 3D-CFD computations with simple prescribed pressure values at the outlets.

The Sacramento River Valley (SRV), valued for its $2.5 billion agricultural production and its biodiversity, is the main supplier of California's water, servicing 25 million people. . Despite rapid changes to the region, little is known about the collective motivations and consequences of land and water use decisions, or the social and environmental vulnerability and resilience of the SRV. The overarching research goal is to examine whether the SRV can continue to supply clean water for California and accommodate agricultural production and biodiversity while coping with climate change and population growth. Without understanding these issues, the resources of the SRV face an uncertain future. The defining goal is to construct a framework that integrates cross-disciplinary and diverse stakeholder perspectives in order to develop a comprehensive understanding of how SRV stakeholders make land and water use decisions. Traditional approaches for modeling have failed to take into consideration multi-scale stakeholder input. Currently there is no effective method to facilitate producers and government agencies in developing a shared representation to address the issues that face the region. To address this gap, researchers and stakeholders are working together to collect and consolidate disconnected knowledge held by stakeholder groups (agencies, irrigation districts, and producers) into a holistic conceptual model of how stakeholders view and make decisions with land and water use under various management systems. Our approach integrates a top-down approach (agency stakeholders) for larger scale management decisions with a conceptual co-creation and data gathering bottom-up approach with local agricultural producer stakeholders for input water and landuse decisions. Land use change models that combine a top-down approach with a bottom-up stakeholder approach are rare and yet essential to understanding how the social process of land use change and ecosystem function are

Carbon Fiber Cementitious Composites (CFCC) is one of the most important materials in smart concrete applications. CFCC should be able to have the piezoresistivity properties where its resistivity changes when there is applied a stress/strain. It must also have the compressive strength qualification. One of the important additives in carbon fiber cementitious composites is dispersant. Dispersion of carbon fiber is one of the key problems in fabricating piezoresistive carbon fiber cementitious composites. In this research, the uses of dispersants are methylcellulose, mixture of defoamer and methylcellulose and superplasticizer based polycarboxylate. The preparation of composite samples is similar as in the mortar technique according to the ASTM C 109/109M standard. The additives material are PAN type carbon fibers, methylcellulose, defoamer and superplasticizer (as water reducer and dispersant). The experimental testing conducts the compressive strength and resistivity at various curing time, i.e. 3, 7 and 28 days. The results obtained that the highest compressive strength value in is for the mortar using superplasticizer based polycarboxylate dispersant. This also shown that the distribution of carbon fiber with superplasticizer is more effective, since not reacting with the cementitious material which was different from the methylcellulose that creates the cement hydration reaction. The research also found that the CFCC require the proper water cement ratio otherwise the compressive strength becomes lower.

Cementitious composites such as concrete pavements are susceptible to different damage modes, which are primarily caused by repeated loading and long-term deterioration. There is even greater concern that damage could worsen and occur more frequently with the use of heavier vehicles or new aircraft carrying greater payloads. Thus, the objective of this research is to engineer cementitious composites with capabilities of self-sensing or detecting damage. The approach was to enhance the damage sensitivity of cementitious composites by incorporating multi-walled carbon nanotubes (MWNT) as part of the mix design and during casting. However, as opposed to directly dispersing MWNTs in the cement matrix, which is the current state-of-art, MWNT-based thin films were airbrushed and coated onto sand particles. The film-coated sand was then used as part of the mix design for casting mortar specimens. Mortar specimens were subjected to compressive cyclic loading tests while their electrical properties were recorded simultaneously. The results showed that the electrical properties of these cementitious composites designed with film-coated sand exhibited extremely high strain sensitivities. The electrical response was also stable and consistent between specimens.

In this paper, a stochastic finite element method (SFEM) is employed to investigate the probability of failure of cementitious buried sewer pipes subjected to combined effect of corrosion and stresses. A non-linear time-dependant model is used to determine the extent of concrete corrosion. Using the SFEM, the effects of different random variables, including loads, pipe material, and corrosion on the remaining safe life of the cementitious sewer pipes are explored. A numerical example is presented to demonstrate the merit of the proposed SFEM in evaluating the effects of the contributing parameters upon the probability of failure of cementitious sewer pipes. The developed SFEM offers many advantages over traditional probabilistic techniques since it does not use any empirical equations in order to determine failure of pipes. The results of the SFEM can help the concerning industry (e.g., water companies) to better plan their resources by providing accurate prediction for the remaining safe life of cementitious sewer pipes. PMID:26068092

In this paper, a stochastic finite element method (SFEM) is employed to investigate the probability of failure of cementitious buried sewer pipes subjected to combined effect of corrosion and stresses. A non-linear time-dependant model is used to determine the extent of concrete corrosion. Using the SFEM, the effects of different random variables, including loads, pipe material, and corrosion on the remaining safe life of the cementitious sewer pipes are explored. A numerical example is presented to demonstrate the merit of the proposed SFEM in evaluating the effects of the contributing parameters upon the probability of failure of cementitious sewer pipes. The developed SFEM offers many advantages over traditional probabilistic techniques since it does not use any empirical equations in order to determine failure of pipes. The results of the SFEM can help the concerning industry (e.g., water companies) to better plan their resources by providing accurate prediction for the remaining safe life of cementitious sewer pipes. PMID:26068092

The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University's Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored on board so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.

The early-age performance of concrete is determined by the properties of the cementitious binder and the evolution of its chemical reactions. The chemical reactivity, and to some extent, the composition of cementitious particles can depend on particle size. Therefore, it is valuable to physically separate cementing minerals into well-defined size classes so that the influences of both particle size and composition on reaction progress can be studied without the confounding effects of a broad particle size distribution. However, conventional particle separation methods (e.g., density fractionation, wet sieving, field-flow extraction, ultrasonification-sedimentation) are time-consuming and cumbersome and result in poor particle yields and size-selectivity, thus, making them unsuitable for processing larger volumes of cementitious powders (on the order of grams). This study applies a novel inertial microfluidics (IMF) based procedure to separate cementitious powders on the basis of their size. Special attention is paid to optimizing operating variables to ensure that particles in a fluid streamline achieve unique equilibrium positions within the device. From such positions, particles can be retrieved as per their size using symmetrical outlet configurations with tuned fluidic resistances. The approach is critically assessed in terms of: (1) its ability to separate cementitious powders into narrow size bins, and therefore its feasibility as a fractionation procedure, and (2) quantitatively relating the operating parameters to the particle yield and size selectivity. The study establishes metrics for assessing the ability of IMF methods to classify minerals and other polydisperse particles on the basis of their size.

Introduction Human injury or infection induces systemic inflammation with characteristic neuro-endocrine responses. Fluctuations in autonomic function during inflammation are reflected by beat-to-beat variation in heart rate, termed heart rate variability (HRV). In the present study, we determine threshold doses of endotoxin needed to induce observable changes in markers of systemic inflammation, we investigate whether metrics of HRV exhibit a differing threshold dose from other inflammatory markers, and we investigate the size of data sets required for meaningful use of multi-scale entropy (MSE) analysis of HRV. Methods Healthy human volunteers (n=25) were randomized to receive placebo (normal saline) or endotoxin/lipopolysaccharide (LPS): 0.1, 0.25, 0.5, 1.0, or 2.0 ng/kg administered intravenously. Vital signs were recorded every 30 minutes for 6 hours and then at 9, 12, and 24 hours after LPS. Blood samples were drawn at specific time points for cytokine measurements. HRV analysis was performed using EKG epochs of 5 minutes. MSE for HRV was calculated for all dose groups to scale factor 40. Results The lowest significant threshold dose was noted in core temperature at 0.25ng/kg. Endogenous TNF-α and IL-6 were significantly responsive at the next dosage level (0.5ng/kg) along with elevations in circulating leukocytes and heart rate. Responses were exaggerated at higher doses (1 and 2 ng/kg). Time domain and frequency domain HRV metrics similarly suggested a threshold dose, differing from placebo at 1.0 and 2.0 ng/kg, below which no clear pattern in response was evident. By applying repeated-measures ANOVA across scale factors, a significant decrease in MSE was seen at 1.0 and 2.0 ng/kg by 2 hours post exposure to LPS. While not statistically significant below 1.0 ng/kg, MSE unexpectedly decreased across all groups in an orderly dose-response pattern not seen in the other outcomes. Conclusions By usingrANOVA across scale factors, MSE can detect autonomic change

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

Processes regulating the cardiovascular system (CVS) are numerous. Each possesses several temporal scales. Their interactions lead to interdependences across multiple scales. For the CVS analysis, different multiscale studies have been proposed, mostly performed on heart rate variability signals (HRV) reflecting the central CVS; only few were dedicated to data from the peripheral CVS, such as laser Doppler flowmetry (LDF) signals. Very recently, a study implemented the first computation of multiscale entropy for LDF signals. A nonmonotonic evolution of multiscale entropy with two distinctive scales was reported, leading to a markedly different behavior from the one of HRV. Our goal herein is to confirm these results and to go forward in the investigations on origins of this behavior. For this purpose, 12 LDF signals recorded simultaneously on the two forearms of six healthy subjects are processed. This is performed before and after application of physiological scales-based filters aiming at isolating previously found frequency bands linked to physiological activities. The results obtained with signals recorded simultaneously on two different sites of each subject show a probable central origin for the nonmonotonic behavior. The filtering results lead to the suggestion that origins of the distinctive scales could be dominated by the cardiac activity. PMID:21712149

Predicting the geomechanical response of geological formations to thermal, pressure, and mechanical loading is important in many engineering applications. The mathematical formulation that describes deformation of a reservoir coupled with flow and transport entails heterogeneous coefficients with a wide range of length scales. Such detailed heterogeneous descriptions of reservoir properties impose severe computational challenges for the study of realistic-scale (km) reservoirs. To deal with these challenges, we developed an Algebraic Multiscale Solver for ELastic geomechanical deformation (EL-AMS). Constructed on finite element fine-scale system, EL-AMS imposes a coarse-scale grid, which is a non-overlapping decomposition of the domain. Then, local (coarse) basis functions for the displacement vector are introduced. These basis functions honor the elastic properties of the local domains subject to the imposed local boundary conditions. The basis form the Restriction and Prolongation operators. These operators allow for the construction of accurate coarse-scale systems for the displacement. While the multiscalesystem is efficient for resolving low-frequency errors, coupling it with a fine-scale smoother, e.g., ILU(0), leads to an efficient iterative solver. Numerical results for several test cases illustrate that EL-AMS is quite efficient and applicable to simulate elastic deformation of large-scale heterogeneous reservoirs.

Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

The U.S. Environmental Protection Agency’s (EPA) multi-scale infrastructure assessment project supports both water resource adaptation to climate change and the rehabilitation of the nation’s aging water infrastructure by providing tools, scientific data and information to progra...

This report describes work performed by the Savannah River National Laboratory (SRNL) in fiscal year 2014 to develop a new Cementitious Barriers Project (CBP) software module designated as FLOExcel. FLOExcel incorporates a uniform database to capture material characterization data and a GoldSim model to define flow properties for both intact and fractured cementitious materials and estimate Darcy velocity based on specified hydraulic head gradient and matric tension. The software module includes hydraulic parameters for intact cementitious and granular materials in the database and a standalone GoldSim framework to manipulate the data. The database will be updated with new data as it comes available. The software module will later be integrated into the next release of the CBP Toolbox, Version 3.0. This report documents the development efforts for this software module. The FY14 activities described in this report focused on the following two items that form the FLOExcel package; 1) Development of a uniform database to capture CBP data for cementitious materials. In particular, the inclusion and use of hydraulic properties of the materials are emphasized; and 2) Development of algorithms and a GoldSim User Interface to calculate hydraulic flow properties of degraded and fractured cementitious materials. Hydraulic properties are required in a simulation of flow through cementitious materials such as Saltstone, waste tank fill grout, and concrete barriers. At SRNL these simulations have been performed using the PORFLOW code as part of Performance Assessments for salt waste disposal and waste tank closure.

Engineered barriers including cementitious barriers are used at sites disposing or contaminated with low-level radioactive waste to enhance performance of the natural environment with respect to controlling the potential spread of contaminants. Drivers for using cementitious barriers include: high radionuclide inventory, radionuclide characteristics (e.g., long half-live, high mobility due to chemical form/speciation, waste matrix properties, shallow water table, and humid climate that provides water for leaching the waste). This document comprises the first in a series of reports being prepared for the Cementitious Barriers Partnership. The document is divided into two parts which provide a summary of: (1) existing experience in the assessment of performance of cementitious materials used for radioactive waste management and disposal and (2) sensitivity and uncertainty analysis approaches that have been applied for assessments. Each chapter is organized into five parts: Introduction, Regulatory Considerations, Specific Examples, Summary of Modeling Approaches and Conclusions and Needs. The objective of the report is to provide perspective on the state of the practice for conducting assessments for facilities involving cementitious barriers and to identify opportunities for improvements to the existing approaches. Examples are provided in two contexts: (1) performance assessments conducted for waste disposal facilities and (2) performance assessment-like analyses (e.g., risk assessments) conducted under other regulatory regimes. The introductory sections of each section provide a perspective on the purpose of performance assessments and different roles of cementitious materials for radioactive waste management. Significant experience with assessments of cementitious materials associated with radioactive waste disposal concepts exists in the US Department of Energy Complex and the commercial nuclear sector. Recently, the desire to close legacy facilities has created

The high-temperature in vitrification process of radioactive wastes could cause radioactive technetium ( 99Tc) in secondary liquid wastes to become volatile. Solidified cementitious waste forms at low temperature were developed to immobilize radioactive secondary waste. This research focuses on the characterization of a cementitious waste form called Cast Stone. Properties including compressive strength, surface area, phase composition, and technetium leaching were measured. The results indicate that technetium diffusivity is affected by simulant type. Additionally, ettringite and AFm (Al 2O 3-Fe 2O 3-mono) main crystalline phases were formed during hydration. The Cast Stone waste form passed the qualification requirements for a secondary waste form, which are compressive strength of 3.45 MPa and technetium diffusivity of 10 -9 cm 2/s. Cast Stone was found to be a good candidate for immobilizing secondary waste streams.

Different types of healing agents have already been tested on their efficiency for use in self-healing cementitious materials. Generally, commercial healing agents are used while their properties are adjusted for manual crack repair and not for autonomous crack healing. Consequently, the amount of regain in properties due to self-healing of cracks is limited. In this research, a methyl methacrylate (MMA)-based healing agent was developed specifically for use in self-healing cementitious materials. Various parameters were optimized including the viscosity, curing time, strength, etc. After the desired properties were obtained, the healing agent was encapsulated and screened for its self-healing efficiency. The decrease in water permeability due to autonomous crack healing using MMA as a healing agent was similar to the results obtained for manually healed cracks. First results seem promising: however, further research needs to be undertaken in order to obtain an optimal healing agent ready for use in practice.

Carbonation efficiency was evaluated for three cementitious materials having different CaO-bearing minerals (lime, Portland cement and waste concrete) using various extraction reagents (HCl, CH3COOH, NH4Cl and deionized water). The cementitious materials were subjected to Ca extraction and carbonation tests under ambient pressure and temperature conditions. The Ca extraction efficiency generally decreased in the order lime, Portland cement and waste concrete, regardless of the extraction solution. Among the extraction solutions, NH4Cl was the most effective for Ca extraction and carbonation. The results of this study suggest that the types of extraction solution and CaO-bearing mineral of the materials are primary factors affecting carbonation efficiency. PMID:22856314

The objectives of this limited study were to: (1) review the potential for degradation of cementitious materials due to exposure to high concentrations of phosphate ions; (2) provide an improved understanding of any significant factors that may lead to a requirement to establish exposure limits for concrete structures exposed to soils or ground waters containing high levels of phosphate ions; (3) recommend, as appropriate, whether a limitation on phosphate ion concentration in soils or ground water is required to avoid degradation of concrete structures; and (4) provide a "primer" on factors that can affect the durability of concrete materials and structures in nuclear power plants. An assessment of the potential effects of phosphate ions on cementitious materials was made through a review of the literature, contacts with concrete research personnel, and conduct of a "bench-scale" laboratory investigation. Results of these activities indicate that: no harmful interactions occur between phosphates and cementitious materials unless phosphates are present in the form of phosphoric acid; phosphates have been incorporated into concrete as set retarders, and phosphate cements have been used for infrastructure repair; no standards or guidelines exist pertaining to applications of reinforced concrete structures in high-phosphate environments; interactions of phosphate ions and cementitious materials has not been a concern of the research community; and laboratory results indicate similar performance of specimens cured in phosphate solutions and those cured in a calcium hydroxide solution after exposure periods of up to eighteen months. Relative to the "primer," a separate NUREG report has been prepared that provides a review of pertinent factors that can affect the durability of nuclear power plant reinforced concrete structures.

Incorporation of living organisms, such as photosynthetic organisms, on the structure envelope has become a priority in the area of architecture and construction due to aesthetical, economic and ecological advantages. Important research efforts are made to achieve further improvements, such as for the development of cementitious materials with an enhanced bioreceptivity to stimulate biological growth. Previously, the study of the bioreceptivity of cementitious materials has been carried out mainly under laboratory conditions although field-scale experiments may present different results. This work aims at analysing the colonisation of cementitious materials with different levels of bioreceptivity by placing them in three different environmental conditions. Specimens did not present visual colonisation, which indicates that environmental conditions have a greater impact than intrinsic properties of the material at this stage. Therefore, it appears that in addition to an optimized bioreceptivity of the concrete (i.e., composition, porosity and roughness), extra measures are indispensable for a rapid development of biological growth on concrete surfaces. An analysis of the colonisation in terms of genus and quantity of the most representative microorganisms found on the specimens for each location was carried out and related to weather conditions, such as monthly average temperature and total precipitation, and air quality in terms of NOx, SO2, CO and O3. OPC-based specimens presented a higher colonisation regarding both biodiversity and quantity. However, results obtained in a previous experimental programme under laboratory conditions suggested a higher suitability of Magnesium Phosphate Cement-based (MPC-based) specimens for algal growth. Consequently, carefully considering the environment and the relationships between the different organisms present in an environment is vital for successfully using a cementitious material as a substrate for biological growth. PMID

Background Cellular processes such as metabolism, decision making in development and differentiation, signalling, etc., can be modeled as large networks of biochemical reactions. In order to understand the functioning of these systems, there is a strong need for general model reduction techniques allowing to simplify models without loosing their main properties. In systems biology we also need to compare models or to couple them as parts of larger models. In these situations reduction to a common level of complexity is needed. Results We propose a systematic treatment of model reduction of multiscale biochemical networks. First, we consider linear kinetic models, which appear as "pseudo-monomolecular" subsystems of multiscale nonlinear reaction networks. For such linear models, we propose a reduction algorithm which is based on a generalized theory of the limiting step that we have developed in [1]. Second, for non-linear systems we develop an algorithm based on dominant solutions of quasi-stationarity equations. For oscillating systems, quasi-stationarity and averaging are combined to eliminate time scales much faster and much slower than the period of the oscillations. In all cases, we obtain robust simplifications and also identify the critical parameters of the model. The methods are demonstrated for simple examples and for a more complex model of NF-κB pathway. Conclusion Our approach allows critical parameter identification and produces hierarchies of models. Hierarchical modeling is important in "middle-out" approaches when there is need to zoom in and out several levels of complexity. Critical parameter identification is an important issue in systems biology with potential applications to biological control and therapeutics. Our approach also deals naturally with the presence of multiple time scales, which is a general property of systems biology models. PMID:18854041

Fiber reinforced cementitious composite (FRCC) materials have been widely used during last decades in order to overcome some of traditional cementitious materials issues: brittle behaviour, fire resistance, cover spalling, impact strength. For composite materials, fiber/matrix bond plays an important role because by increasing fiber/matrix interactions is possible to increase the behaviour of the entire material. In this study, in order to improve fiber to matrix adhesion, two chemical treatments of polypropylene fibers were investigated: alkaline hydrolysis and nano-silica sol-gel particles deposition. Treatmtents effect on fibers morphology and mechanical properties was investigated by scanning electron microscopy (SEM) and tensile tests. SEM investigations report the presence of spherical nano-silica particles on fiber surface, in the case of sol-gel process, while alkaline hydrolysis leads to an increase of fibers roughness. Both treatments have negligible influence on fibers mechanical properties confirming the possibility of their use in a cementitious mortar. Pullout tests were carried out considering three embedded length of fibers in mortar samples (10, 20 and 30 mm, respectively) showing an increase of pullout energy for treated fibers. The influence on fiber reinforced mortar mechanical properties was investigated by three-point flexural tests on prismatic specimens considering two fibers length (15 and 30 mm) and two fibers volume fractions (0.50 and 1.00 %). A general increase of flexural strength over the reference mix was achieved and an overall better behaviour is recognizable for mortars containing treated fibers.

Caltrans specifications for the construction of rigid pavements require rapid setting, high early strength, superior workability concrete with a desired 30+ year service life. These strict specifications provide the motivations for the investigation of advanced cementitious materials for pavement construction. The cementitious materials under consideration by Caltrans may be classified into four categories: Portland cements and blends, calcium aluminate cements and blends, calcium sulfoaluminate cements, and fly ash-based cements. To achieve the desired 30+ year design life, it is essential to select materials that are expected to exhibit long-term durability. Because most of the cementitious materials under consideration have not been extensively used for pavement construction in the United States, it is essential to characterize the long-term durability of each material. This report provides general information concerning the deleterious reactions that may damage concrete pavements in California. The reactions addressed in this report are sulfate attack, aggregate reactions, corrosion of reinforcing steel, and freeze-thaw action. Specifically, the expected performance of Portland cements and blends, calcium aluminate cements and blends, calcium sulfoaluminate cements, and fly ash-based cements are examined with regard to each of the deleterious reactions listed. Additional consideration is given to any deterioration mechanism that is particular to any of these cement types. Finally, the recommended test program for assessing potential long-term durability with respect to sulfate attack is described.

Fiber reinforced cementitious composite (FRCC) materials have been widely used during last decades in order to overcome some of traditional cementitious materials issues: brittle behaviour, fire resistance, cover spalling, impact strength. For composite materials, fiber/matrix bond plays an important role because by increasing fiber/matrix interactions is possible to increase the behaviour of the entire material. In this study, in order to improve fiber to matrix adhesion, two chemical treatments of polypropylene fibers were investigated: alkaline hydrolysis and nano-silica sol-gel particles deposition. Treatmtents effect on fibers morphology and mechanical properties was investigated by scanning electron microscopy (SEM) and tensile tests. SEM investigations report the presence of spherical nano-silica particles on fiber surface, in the case of sol-gel process, while alkaline hydrolysis leads to an increase of fibers roughness. Both treatments have negligible influence on fibers mechanical properties confirming the possibility of their use in a cementitious mortar. Pullout tests were carried out considering three embedded length of fibers in mortar samples (10, 20 and 30 mm, respectively) showing an increase of pullout energy for treated fibers. The influence on fiber reinforced mortar mechanical properties was investigated by three-point flexural tests on prismatic specimens considering two fibers length (15 and 30 mm) and two fibers volume fractions (0.50 and 1.00 %). A general increase of flexural strength over the reference mix was achieved and an overall better behaviour is recognizable for mortars containing treated fibers.

High-efficiency recovery and utilization of steel slag are important concerns for environmental protection and sustainable development. To establish a rapid method to evaluate the cementitious properties of steel slag, leaching tests were carried out on steel slag components via an evaporation-condensation method; the leaching characteristics and mechanism of the slag were also investigated. The relationship between leaching characteristics and cementitious properties, which were represented by mortar compressive strength, was analyzed. Results show that there exist significant differences among the amounts of chemically active leached components. The leaching process can be described by the shrinking unreacted core model controlled by intra-particle diffusion, and is in accordance with Kondo R hydration kinetics equation. The leaching process showed a good linear relationship between the amounts of components leached from steel slag and the mortar compressive strength of cementitious materials prepared from reference cement and steel slag with mass ratios of 50:50 and 70:30. The compressive strengths of mortars subjected to 7, 28, and 90 days of curing can be accurately predicted by the sum of leached (CaO+Al(2)O(3)) obtained after a certain length of leaching time. PMID:22088502

The mechanical and constitutive response of materials like cement, and bio materials like fish scale and abalone shell is very complex due to heterogeneities that are inherently present in the nano and microstructures. The intrinsic constitutive behaviors are driven by the chemical composition and the molecular, micro, and meso structures. Therefore, it becomes important to identify the material genome as the building block for the material. For instance, in cementitious materials, the genome of C-S-H phase (the glue or the paste) that holds the various clinkers, such as the dicalcium silicate, tricalcium silicate, calcium ferroaluminates, and others is extremely complex. Often mechanical behaviors of C-S-H type materials are influenced by the chemistry and the structures at all nano to micro length scales. By explicitly modeling the molecular structures using appropriate potentials, it is then possible to compute the elastic tensor from molecular dynamics simulations using all atom method. The elastic tensors for the C-S-H gel and other clinkers are determined using the software suite ``Accelrys Materials Studio.'' A strain rate dependent, fracture mechanics based tensile damage model has been incorporated into ABAQUS finite element code to model spall evolution in the heterogeneous cementitious material with all constituents explicitly modeled through one micron element resolution. This paper presents results from nano/micro/meso scale analyses of shock wave propagation in a heterogeneous cementitious material using both molecular dynamic and finite element codes.

This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle

In this thesis, we develop and analyze a heterogeneous multiscale model for coupled fluid flow and solid deformation in porous media based on operator splitting and finite volume method. The splitting method results in two elliptic multiscale PDE's in the form of a reaction diffusion equation and a linear elasticity equation. We extend our previous multiscale method from 1D to higher dimensions and develop new approaches for the inclusion of mixed boundary conditions and source terms. We derive an error estimate for our multiscale method and analyze the stability of our splitting method. We also test the effectiveness of our method in the case of steady state linear poroelasticity.

The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.

The United States Department of Energy (US DOE) concept for facility in-situ decommissioning (ISD) is to physically stabilize and isolate in tact, structurally sound facilities that are no longer needed for their original purpose of, i.e., producing (reactor facilities), processing (isotope separation facilities) or storing radioactive materials. The Savannah River Site 105-P and 105-R Reactor Facility ISD requires about 250,000 cubic yards of grout to fill the below grade structure. The fills are designed to prevent subsidence, reduce water infiltration, and isolate contaminated materials. This work is being performed as a Comprehensive Environmental Response, Compensations and Liability Act (CERCLA) action and is part of the overall soil and groundwater completion projects for P- and R-Areas. Cementitious materials were designed for the following applications: (1) Below grade massive voids/rooms: Portland cement-based structural flowable fills for - Bulk filling, Restricted placement and Underwater placement. (2) Special below grade applications for reduced load bearing capacity needs: Cellular portland cement lightweight fill (3) Reactor vessel fills that are compatible with reactive metal (aluminum metal) components in the reactor vessels: Calcium sulfoaluminate flowable fill, and Magnesium potassium phosphate flowable fill. (4) Caps to prevent water infiltration and intrusion into areas with the highest levels of radionuclides: Portland cement based shrinkage compensating concrete. A system engineering approach was used to identify functions and requirements of the fill and capping materials. Laboratory testing was performed to identify candidate formulations and develop final design mixes. Scale-up testing was performed to verify material production and placement as well as fresh and cured properties. The 105-P and 105-R ISD projects are currently in progress and are expected to be complete in 2012. The focus of this paper is to describe the (1) grout mixes

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents results of studies used in the development of a multi-scale visualization methodology. First we use streamlines to show the path the flow is taking as it moves through the system, including the aneurysm. Next we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of the aneurysm

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. PMID:26548944

The Mid Atlantic Ridge (MAR) has been identified as an important component of the lower bathyal (800-3500 m depth) benthic biogeographic province in the North Atlantic Ocean. We performed a multi-scale characterization of seafloor topography of the MAR. In the basin-scale analysis, we have used the 30″ General Bathymetric Chart of the Oceans (GEBCO) grid to estimate the area of different components of lower bathyal habitat in the main North Atlantic basin and to produce a corresponding depth-area relationship. The regional-scale investigation is based on swath bathymetry surveys which show the flanks to MAR to comprise a series of sediment-draped flat plains (37.65% of area) with intervening gentle slopes ranging from 5° to 30° (56.70% of area) and slopes steeper than 30° (5.65% of area). The steep slopes have significant areas of hard substrate (70%) comprising bare cliff faces and rock outcrops. Within the local-scale approach, detailed surveys of such steep areas were done by multi-beam sonar and cameras mounted on a Remotely Operated Vehicle (ROV). In several locations, the terrace-like seafloor topography has also been identified. Overall, it has been shown that the MAR lower bathyal is 95% covered with soft sediment.

Waste sludge, a solid recovered from wastewater of photovoltaic-industries, composes of agglomerates of nano-particles like SiO{sub 2} and CaCO{sub 3}. This sludge deflocculates in aqueous solutions into nano-particles smaller than 1 μm. Thus, this sludge constitutes a potentially hazardous waste when it is improperly disposed. Due to its high content of amorphous SiO{sub 2}, this sludge has a potential use as supplementary cementitious material (SCM) in concrete. In this study the main properties of three different samples of photovoltaic's silica-rich waste sludge (nSS) were physically and chemically characterized. The characterization techniques included: scanning electron microscopy (SEM), X-ray energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), nitrogen physical adsorption isotherm (BET method), density by Helium pycnometry, particle size distribution determined by laser light scattering (LLS) and zeta-potential measurements by dynamic light scattering (DLS). In addition, a dispersability study was performed to design stable slurries to be used as liquid additives for the concrete production on site. The effects on the hydration kinetics of cement pastes by the incorporation of nSS in the designed slurries were determined using an isothermal calorimeter. A compressive strength test of standard mortars with 7% of cement replacement was performed to determine the pozzolanic activity of the waste nano-silica sludge. Finally, the hardened system was fully characterized to determine the phase composition. The results demonstrate that the nSS can be utilized as SCM to replace portion of cement in mortars, thereby decreasing the CO{sub 2} footprint and the environmental impact of concrete. -- Highlights: •Three different samples of PV nano-silica sludge (nSS) were fully characterized. •nSS is composed of agglomerates of nano-particles like SiO{sub 2} and CaCO{sub 3}. •Dispersability studies demonstrated that nSS agglomerates are broken to nano

Visual examination of chromosome banding patterns is an important means of chromosome analysis. Cytogeneticists compare their patient's chromosome image against the prototype normal/abnormal human chromosome banding patterns. Automated chromosome analysis instruments facilitate this by digitally enhancing the chromosome images. Currently available systems employing traditional highpass/bandpass filtering and/or histogram equalization are approximately equivalent to photomicroscopy in their ability to support the detection of band pattern alterations. Improvements in chromosome image display quality, particularly in the detail of the banding pattern, would significantly increase the cost-effectiveness of these systems. In this paper we present our work on the use of multiscale transform and derivative filtering for image enhancement of chromosome banding patterns. A steerable pyramid representation of the chromosome image is generated by a multiscale transform. The derivative filters are designed to detect the bands of a chromosome, and the steerable pyramid transform is chosen based on its desirable properties of shift and rotation invariance. By processing the transform coefficients that correspond to the bands of the chromosome in the pyramid representation, contrast enhancement of the chromosome bands can be achieved with designed flexibility in scale, orientation and location. Compared with existing chromosome image enhancement techniques, this new approach offers the advantage of selective chromosome banding pattern enhancement that allows designated detail analysis. Experimental results indicate improved enhancement capabilities and promise more effective visual aid to comparison of chromosomes to the prototypes and to each other. This will increase the ability of automated chromosome analysis instruments to assist the evaluation of chromosome abnormalities in clinical samples.

The nucleosome core particle (NCP) is the basic building block of chromatin. Under the influence of multivalent cations, isolated mononucleosomes exhibit a rich phase behaviour forming various columnar phases with characteristic NCP-NCP stacking. NCP stacking is also a regular element of chromatin structure in vivo. Understanding the mechanism of nucleosome stacking and the conditions leading to self-assembly of NCPs is still incomplete. Due to the complexity of the system and the need to describe electrostatics properly by including the explicit mobile ions, novel modelling approaches based on coarse-grained (CG) methods at the multiscale level becomes a necessity. In this work we present a multiscale CG computer simulation approach to modelling interactions and self-assembly of solutions of NCPs induced by the presence of multivalent cations. Starting from continuum simulations including explicit three-valent cobalt(III)hexammine (CoHex3+) counterions and 20 NCPs, based on a previously developed advanced CG NCP model with one bead per amino acid and five beads per two DNA base pair unit (Fan et al 2013 PLoS One 8 e54228), we use the inverse Monte Carlo method to calculate effective interaction potentials for a ‘super-CG’ NCP model consisting of seven beads for each NCP. These interaction potentials are used in large-scale simulations of up to 5000 NCPs, modelling self-assembly induced by CoHex3+. The systems of ‘super-CG’ NCPs form a single large cluster of stacked NCPs without long-range order in agreement with experimental data for NCPs precipitated by the three-valent polyamine, spermidine3+.

The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.

An in vivo axial loading model of the rat ulna was developed almost two decades ago. As a minimally invasive model, it lends itself particularly well for the study of functional adaptation in bone and the interosseous membrane, a ligament spanning between the radius and ulna. The objective of this paper is to review computational and experimental approaches to elucidate its applicability for the study of multiscale bone and ligament mechanobiology. Specifically, this review describes approaches, including i) measurement of strains on bone tissue surfaces, ii) development of a three-dimensional finite element (FE) mesh of a skeletally mature rat ulna, iii) parametric study of the relative influence of mechanical constants and materials properties on computational model predictions, iv) comparison of experimental and computational strain distribution data, and analysis of the radius and interosseous membrane (IOM) ligament's effect on axial load distribution through the ulna of the rat, and v) the effect of mechanical loading on transport through the IOM using different molecular weight fluorescent tagged dextrans. In the first stage of the study a computational stress analysis was performed after applying a 20 N single static load at the ulnar extremities, corresponding to values of experimental strain gauge measurements. To account for the anisotropy of the bone matrix, transverse isotraopic, elastic material properties were applied. In a parametric study, we analyzed the qualitative effect of different material properties on the global load and displacement behavior of the computational model. In a second stage, the same ulnar model used in the parametric study was extended to account for the interaction between the ulna, radius and IOM. The three-dimensional FE model of the rat forelimb confirms the influence of ulnar curvature on its deformation and underscores the influence of the radius and IOM on strain distribution through the ulna. The mode of strain, {i

This paper presents our work in the concept exploration of a new family of self-healing materials that hold promise for "crack-free" cementitious composites. This innovative system features the design of passive smart microcapsules with oil core and silica gel shell, prepared through an interfacial self-assembly process and sol-gel reaction. Methylmethacrylate monomer and triethylborane were chosen as the healing agent and the catalyst, and were microencapsulated respectively. The microcapsules were dispersed in fresh cement mortar along with carbon microfibers. For the hardened mortar, self-healing can be triggered by crack propagation through the microcapsules, which then releases the healing agent and the catalyst into the microcracks. Polymerization of the healing agent is initiated by contact with the catalyst, bonding the crack faces. Surface analytical tools such as optical microscope and field emission scanning electron microscope were used to examine the localized morphology and encapsulation of the passive smart microcapsules. The self-healing effect was evaluated using gas permeability and electrochemical impedance measurements.

The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. The default parameterization of threshold friction velocity constants in the CMAQ are revised to avoid double counting of the impact of soil moisture based on the re-analysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is implemented to simulate the reactions involving dust aerosol. The improved dust module in the CMAQ was applied over East Asia for March and April from 2006 to 2010. Evaluation against observations has demonstrated that simulation bias of PM10 and aerosol optical depth (AOD) is reduced from -55.42 and -31.97 % in the original CMAQ to -16.05 and -22.1 % in the revised CMAQ, respectively. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry is also found to result in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). Investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variations of dust aerosols. Model evaluation indicates potential uncertainties within the excessive soil moisture fraction used by meteorological simulation. The mass contribution of fine mode aerosol in dust emission may be underestimated by 50 %. The revised revised CMAQ provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East

The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from -55.42 and -31.97 % by the original CMAQ to -16.05 and -22.1 % by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50 %. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.

In the photosynthetic electron transfer (ET) chain, two electrons transfer from photosystem I to the flavin-dependent ferredoxin-NADP(+) reductase (FNR) via two sequential independent ferredoxin (Fd) electron carriers. In some algae and cyanobacteria (as Anabaena), under low iron conditions, flavodoxin (Fld) replaces Fd as single electron carrier. Extensive mutational studies have characterized the protein-protein interaction in FNR/Fd and FNR/Fld complexes. Interestingly, even though Fd and Fld share the interaction site on FNR, individual residues on FNR do not participate to the same extent in the interaction with each of the protein partners, pointing to different electron transfer mechanisms. Despite of extensive mutational studies, only FNR/Fd X-ray structures from Anabaena and maize have been solved; structural data for FNR/Fld remains elusive. Here, we present a multiscale modelling approach including coarse-grained and all-atom protein-protein docking, the QM/MM e-Pathway analysis and electronic coupling calculations, allowing for a molecular and electronic comprehensive analysis of the ET process in both complexes. Our results, consistent with experimental mutational data, reveal the ET in FNR/Fd proceeding through a bridge-mediated mechanism in a dominant protein-protein complex, where transfer of the electron is facilitated by Fd loop-residues 40-49. In FNR/Fld, however, we observe a direct transfer between redox cofactors and less complex specificity than in Fd; more than one orientation in the encounter complex can be efficient in ET. PMID:26385068

The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the

With the rapid development of electrical circuits, Micro electromechanical system (MEMS) and network technology, wireless smart sensor networks (WSSN) have shown significant potential for replacing existing wired Structural health monitoring (SHM) systems due to their cost effectiveness and versatility. A few structural systems have been monitored using WSSN measuring acceleration, temperature, wind speed, humidity; however, a multi-scale sensing device which has the capability to measure the displacement has not been yet developed. In this project, a new highaccuracy displacement sensing system has been developed combining a high resolution analog displacement sensor and MEMS-based wireless microprocessor platform. The wireless sensor is calibrated in the laboratory to get the high precision displacement data from analog sensor. The developed multi-scale sensing system is evaluated in a laboratory bridge structure to check its performance. Finally, the developed hybrid multi-scale displacement sensing system was deployed on in-service highway bridge for SHM.

The power of multiscale fluid simulations lies in its ability to recover a hierarchical levels of details by choreographing multiple solvers, thus extending the length and time scale accessible given a fixed amount of computing power. However, practical difficulties frequently arise when stitching together solvers which were not designed to be coupled, and would often result in tedious and unsustainable coding effort. The Multiscale Universal Interface (MUI) aims to solve this problem by exposing a small set of generalized programming interfaces that can be dropped into existing solvers with minimal intrusion. Three deployment cases will be given for demonstrating real-world applications of MUI. In the first case we used MUI to implement simulations of polymer-grafted surface in flow using Smoothed Particle Hydrodynamics/Dissipative Particle Dynamics (SPH/DPD) and state variable coupling. In the second case we constructed coupled DPD/Finite Element Method (FEM) simulation of conjugate heat transfer in heterogeneous coolant. In the third case we built hybrid DPD/molecular dynamics (MD) simulations by blending the forces on atoms at interface regions. Supported by the DOE Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) and AFOSR FA9550-12-1-0463. Computer hours at ORNL allocated through INCITE BIP118 and DD102.

Clustering is the preferred choice of method in many applications, and support vector clustering (SVC) has proven efficient for clustering noisy and high-dimensional data sets. A method for multiscale support vector clustering is demonstrated, using the recently emerged method for fast calculation of the entire regularization path of the support vector domain description. The method is illustrated on artificially generated examples, and applied for detecting blood vessels from high resolution time series of magnetic resonance imaging data. The obtained results are robust while the need for parameter estimation is reduced, compared to support vector clustering.

The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shockmore » waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.« less

This experimental research was to investigate the possibility of incorporating red mud and coal gangue as raw materials for the production of red mud-coal gangue cementitious material, abbreviated as RGC, including analyses of its chemical composition, physical properties, mechanical properties and hydration products. The red mud and coal gangue (at a ratio of 3:2) were mixed together and shaped in small spheres with a water to solid ratio of 0.30 and then calcined at 600 degrees C for 2h. Subsequently, the RGC was prepared by blending 50% the resultant red mud-coal gangue mixtures, 24% blast-furnace slag, 20% clinker and 6% gypsum. The hydration products of RGC were characterized by XRD, TG-DTA and SEM-EDS. The results showed that it is feasible to use red mud and coal gangue to replace up to 50% of the raw materials to produce cementitious material, which can be called as silica-alumina based cementitious material. The hydration products of RGC are mostly ettringite, calcium hydroxide and C-S-H gel. As the dominant products, C-S-H gel and ettringite are principally responsible for the strength development of RGC in early hydration process. The content of Ca(OH)(2) initially increased but later was depleted after reaching the peak value at 21 days. Moreover, it is found that the composition of the C-S-H gel shifted towards higher Si, Al and Na contents with the increase of hydration age, whereas that of Ca shifted towards lower content. PMID:19237241

Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion [1-3] which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach. PMID:19735554

The influence of different cooling regimes (quenching in water and cooling in air) on the residual mechanical properties of engineered cementitious composite (ECC) subjected to high temperature up to 800°C was discussed in this paper. The ECC specimens are exposed to 100, 200, 400, 600, and 800°C with the unheated specimens for reference. Different cooling regimens had a significant influence on the mechanical properties of postfire ECC specimens. The microstructural characterization was examined before and after exposure to fire deterioration by using scanning electron microscopy (SEM). Results from the microtest well explained the mechanical properties variation of postfire specimens. PMID:25161392

The current plans for the Yucca Mountain (YM) repository project (YMP) use steel structures to stabilize the disposal drifts and connecting tunnels that are collectively over 100 kilometers in length. The potential exist to reduce the underground construction cost by 100s of millions of dollars and improve the repository's performance. These economic and engineering goals can be achieved by using the appropriate cementitious materials to build out these tunnels. This report describes the required properties of YM compatible cements and reviews the literature that proves the efficacy of this approach. This report also describes a comprehensive program to develop and test materials for a suite of underground construction technologies.

A robust numerical solution of the nonlinear Poisson-Boltzmann equation for asymmetric polyelectrolyte solutions in discrete pore geometries is presented. Comparisons to the linearized approximation of the Poisson-Boltzmann equation reveal that the assumptions leading to linearization may not be appropriate for the electrochemical regime in many cementitious materials. Implications of the electric double layer on both partitioning of species and on diffusive release are discussed. The influence of the electric double layer on anion diffusion relative to cation diffusion is examined.

The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author

To improve the precision of nerve segmentation in CT images, a new comparability function is proposed in this paper to enhance the contrast between nerve structure and other surrounding tissues. It is based on nerve's characteristic, i.e. dark tubular structure, and a thorough analysis of the multi-scale Hessian matrix. By comparability function, the gray range of interested nerve structure can be automatically determined, which combines the multi-scale Hessian matrix eigenvalues with intensity information of original nerve CT images. The experimental results show that the improved algorithm can not only enhance the continuous nerve of tubular structure, but also clearly reflect its bifurcations and crossovers. It is very important and significant to the computer-aided disease diagnosis of peripheral nervous system.

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. PMID:23996238

In recent years, polymer nano-composites (PNCs) have increasingly gained more attention due to their improved mechanical, barrier, thermal, optical, electrical and biodegradable properties in comparison with the conventional micro-composites or pristine polymer. With a modest addition of nanoparticles (usually less than 5wt. %), PNCs offer a wide range of improvements in moduli, strength, heat resistance, biodegradability, as well as decrease in gas permeability and flammability. Although PNCs offer enormous opportunities to design novel material systems, development of an effective numerical modeling approach to predict their properties based on their complex multi-phase and multiscale structure is still at an early stage. Developing a computational framework to predict the mechanical properties of PNC is the focus of this dissertation. A computational framework has been developed to predict mechanical properties of polymer nano-composites. In chapter 1, a microstructure inspired material model has been developed based on statistical technique and this technique has been used to reconstruct the microstructure of Halloysite nanotube (HNT) polypropylene composite. This technique also has been used to reconstruct exfoliated Graphene nanoplatelet (xGnP) polymer composite. The model was able to successfully predict the material behavior obtained from experiment. Chapter 2 is the summary of the experimental work to support the numerical work. First, different processing techniques to make the polymer nanocomposites have been reviewed. Among them, melt extrusion followed by injection molding was used to manufacture high density polyethylene (HDPE)---xGnP nanocomposties. Scanning electron microscopy (SEM) also was performed to determine particle size and distribution and to examine fracture surfaces. Particle size was measured from these images and has been used for calculating the probability density function for GNPs in chapter 1. A series of nanoindentation tests have

The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O3, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBCs). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of which are unphysical from the view point of real systems. To cure these problems, we introduce a multi-scale Monte Carlo (MC) method, where ions inside a spherical cavity are simulated explicitly, while ions outside are treated implicitly using a continuum theory. Using the method of Debye charging, we explicitly derive the effective interactions between ions inside the cavity, arising due to the fluctuations of ions outside. We find that these effective interactions consist of two types: (1) a constant cavity potential due to the asymmetry of the electrolyte, and (2) a reaction potential that depends on the positions of all ions inside. Combining the grand canonical Monte Carlo (GCMC) with a recently developed fast algorithm based on image charge method, we perform a multi-scale MC simulation of symmetric electrolytes, and compare it with other simulation methods, including PBC + GCMC method, as well as large scale MC simulation. We demonstrate that our multi-scale MC method is capable of capturing the correct physics of a large system using a small scale simulation.

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

Further developments in the hybrid multiscale energy density method are proposed on the basis of our previous papers. The key points are as follows. (i) The theoretical method for the determination of the weight parameter in the energy coupling equation of transition region in multiscale model is given via constructing underdetermined equations. (ii) By applying the developed mathematical method, the weight parameters have been given and used to treat some problems in homogeneous charge density systems, which are directly related with multiscale science. (iii) A theoretical algorithm has also been presented for treating non-homogeneous systems of charge density. The key to the theoretical computational methods is the decomposition of the electrostatic energy in the total energy of density functional theory for probing the spanning characteristic at atomic scale, layer by layer, by which the choice of chemical elements and the defect complex effect can be understood deeply. (iv) The numerical computational program and design have also been presented. Project supported by the National Basic Research Program of China (Grant No. 2011CB606402) and the National Natural Science Foundation of China (Grant No. 51071091).

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics, and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR, and cryo-electron microscopy, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation, and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger's functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, whereas our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration

The fission products Cs-137 and Sr-90 are amongst the most common radionuclides occurring in ground contamination at the UK civil nuclear sites. Such contamination is often associated with alkaline liquids and the mobility of these fission products may be affected by these chemical conditions. Similar geochemical effects may also result from cementitious leachate associated with building foundations and the use of grouts to remediate ground contamination. The behaviour of fission products in these scenarios is a complex interaction of hydrogeological and geochemical processes. A suite of modelling tools have been developed to investigate the behaviour of a radioactive plume containing Cs and Sr. Firstly the effects of sorption due to cementitious groundwater is modelled using PHREEQC. This chemical model is then incorporated into PHAST for the 3-D reactive solute transport modeling. Results are presented for a generic scenario including features and processes that are likely to be relevant to a number of civil UK nuclear sites. Initial results show that modelling can be a very cost-effective means to study the complex hydrogeological and geochemical processes involved. Modelling can help predict the mobility of contaminants in a range of site end point scenarios, and in assessing the consequences of decommissioning activities. (authors)

The permeability of borehole plug solids and plug-wall rock junctions is a property of major interest in the Borehole Plugging Program. This report describes the equipment and techniques used to determine the permeabilities of possible borehole plugging materials and presents results from tests on various cementitious solids and plug-rock combinations. The cementitious solids were made from mixtures of cement, sand, salt, fly ash, and water. Three different types of cement and four different fly ashes were used. Permeabilities ranged from a high value of 3 x 10/sup -4/ darcy for a neat cement paste to a low of 5 x 10/sup -8/ darcy for a saltcrete containing 30 wt % sodium chloride. Miniature boreholes were made in the following four different types of rock: Westerly granite, Dresser basalt, Sioux quartzite, and St. Cloud granodiorite. These small holes were plugged with a mix consisting of 23 wt % Type I Portland cement, 20 wt % bituminous fy ash, 43.2 wt % sand, and 13.8 wt % water. After curing for 91 days at ambient temperature, the permeability of the plug-wall rock junctions ranged from 3 x 10/sup -5/ to < 1 x 10/sup -8/ darcy. Three of the four miniature plugged boreholes exhibited permeabilities of < 10 microdarcys.

The current work focuses on evaluation of the effective elastic properties of cementitious materials through a voxel based FEA approach. Voxels are generated for a heterogeneous cementitious material (Type-I cement) consisting of typical volume fractions of various constituent phases from digital microstructures. The microstructure is modeled as a micro-scale representative volume element (RVE) in ABAQUS to generate cubes several tens of microns in dimension and subjected to various prescribed deformation modes to generate the effective elastic tensor of the material. The RVE-calculated elastic properties such as moduli and Poisson's ratio are validated through an asymptotic expansion homogenization (AEH) and compared with rule of mixtures. Both Periodic (PBC) and Kinematic boundary conditions (KBC) are investigated to determine if the elastic properties are invariant due to boundary conditions. In addition the method of "Windowing" was used to assess the randomness of the constituents and to validate how the isotropic elastic properties were determined. The average elastic properties obtained from the displacement based FEA of various locally anisotropic micro-size cubes extracted from an RVE of size 100x100x100 microns showed that the overall RVE response was fully isotropic. The effects of domain size, degree of hydration, kinematic and periodic boundary conditions, domain sampling techniques, local anisotropy, particle size distribution (PSD), and random microstructure on elastic properties are studied.

The Federal Facility Compliance Agreement (FFCA) establishes an aggressive schedule for conducting studies and treatment method development under the treatability exclusion of RCRA for those mixed wastes for which treatment methods and capabilities have yet to be defined. One of these wastes is a radioactive cooling tower sludge. This paper presents some results of a treatability study of the stabilization of this cooling tower sludge in cementitious waste forms. The sample of the cooling tower sludge obtained for this study was found to be not characteristically hazardous in regard to arsenic, barium, chromium, lead, and selenium, despite the waste codes associated with this waste. However, the scope of this study included spiking three RCRA metals to two orders of magnitude above the initial concentration to test the limits of cementitious stabilization. Chromium and arsenic were spiked at concentrations of 200, 2,000, and 20,000 mg/kg, and selenium was spiked at 100, 1,000, and 10,000 mg/kg (concentrations based on the metal in the sludge solids). Portland cement, Class F fly ash, and slag were selected as stabilizing agents in the present study. Perlite, a fine, porous volcanic rock commonly used as a filter aid, was used as a water-sorptive agent in this study in order to control bleed water for high water contents. The highly porous perlite dust absorbs large amounts of water by capillary action and does not present the handling and processing problems exhibited by clays used for bleed water control.

The durability of ancient cementitious materials has been investigated to provide data applicable to determining the resistance to weathering of concrete materials for sealing a repository for storage of high-level radioactive waste. Because tuff and volcanic ash are used in the concretes in the vicinity of Rome, the results are especially applicable to a waste repository in tuff. Ancient mortars, plasters, and concretes collected from Rome, Ostia, and Cosa dating to the third century BC show remarkable durability. The aggregates used in the mortars, plasters, and concretes included basic volcanic and pyroclastic rocks (including tuff), terra-cotta, carbonates, sands, and volcanic ash. The matrices of ancient cementitious materials have been characterized and classified into four categories: (1) hydraulic hydrated lime and hydrated lime cements, (2) hydraulic aluminous and ferruginous hydrated lime cements ({plus_minus} siliceous components), (3) pozzolana/hydrated lime cements, and (4) gypsum cements. Most of the materials investigated are in category (3). The materials were characterized to elucidate aspects of the technology that produced them and their response to the environmental exposure throughout their centuries of existence. Their remarkable properties are the result of a combination of chemical, mineralogical, and microstructural factors. Their durability was found to be affected by the matrix mineralogy, particle size, and porosity; aggregate type, grading and proportioning; and the methodology of placement. 30 refs.

This test plan describes activities intended to demonstrate equipment and techniques for producing, injecting, and evaluating microfine cementitious grout. The grout will be injected in fractured rock located below the repository horizon at the Waste Isolation Pilot Plant (WIPP). These data are intended to support the development of the Alcove Gas Barrier System (AGBS), the design of upcoming, large-scale seal tests, and ongoing laboratory evaluations of grouting efficacy. Degradation of the grout will be studied in experiments conducted in parallel with the underground grouting experiment.

In Switzerland, the deep geological disposal in clay-rich rocks is foreseen not only for high-level radioactive waste, but also for intermediate-level (ILW) and low-level (LLW) radioactive waste. Typically, ILW and LLW repositories contain huge amounts of cementitious materials used for waste conditioning, confinement, and as backfill for the emplacement caverns. We are investigating the interactions of such a repository with the surrounding clay rocks and with other clay-rich materials such as sand/bentonite mixtures that are foreseen for backfilling the access tunnels. With the help of a numerical reactive transport model, we are comparing the evolution of cement/clay interfaces for different geochemical and transport conditions. In this work, the reactive transport of chemical components is simulated with the multi-component reactive transport code OpenGeoSys-GEM. It employs the sequential non-iterative approach to couple the mass transport code OpenGeoSys (http://www.ufz.de/index.php?en=18345) with the GEMIPM2K (http://gems.web.psi.ch/) code for thermodynamic modeling of aquatic geochemical systems which is using the Gibbs Energy Minimization (GEM) method. Details regarding code development and verification can be found in Shao et al. (2009). The mineral composition and the pore solution of a CEM I 52.5 N HTS hydrated cement as described by Lothenbach & Wieland (2006) are used as an initial state of the cement compartment. The setup is based on the most recent CEMDATA07 thermodynamic database which includes several ideal solid solutions for hydrated cement minerals and is consistent with the Nagra/PSI thermodynamic database 01/01. The smectite/montmorillonite model includes cation exchange processes and amphotheric≡SOH sites and was calibrated on the basis of data by Bradbury & Baeyens (2002). In other reactive transport codes based on the Law of Mass Action (LMA) for solving geochemical equilibria, cation exchange processes are usually calculated assuming

The Magnetospheric Multiscale (MMS) mission employs four identical spinning spacecraft flying in highly elliptical Earth orbits. These spacecraft will fly in a series of tetrahedral formations with separations of less than 10 km. MMS navigation operations use onboard navigation to satisfy the mission definitive orbit and time determination requirements and in addition to minimize operations cost and complexity. The onboard navigation subsystem consists of the Navigator GPS receiver with Goddard Enhanced Onboard Navigation System (GEONS) software, and an Ultra-Stable Oscillator. The four MMS spacecraft are operated from a single Mission Operations Center, which includes a Flight Dynamics Operations Area (FDOA) that supports MMS navigation operations, as well as maneuver planning, conjunction assessment and attitude ground operations. The System Manager component of the FDOA automates routine operations processes. The GEONS Ground Support System component of the FDOA provides the tools needed to support MMS navigation operations. This paper provides an overview of the MMS mission and associated navigation requirements and constraints and discusses MMS navigation operations and the associated MMS ground system components built to support navigation-related operations.

The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail.

A deep investigation on the hydration mechanism of bauxite-calcination-method red mud-coal gangue based cementitious materials was conducted from viewpoints of hydration products and hydration heat analysis. As a main hydration product, the microstructure of C-A-S-H gel was observed using high resolution transmission electron microscopy. It was found that the C-A-S-H gel is composed of amorphous regions and nanocrystalline regions. Most of regions in the C-A-S-H gel are amorphous with continuous distribution, and the nanocrystalline regions on scale of ∼5nm are dispersed irregularly within the amorphous regions. The hydration heat of red mud-coal gangue based cementitious materials is much lower than that of the ordinary Portland cement. A hydration model was proposed for this kind of cementitious materials, and the hydration process mainly consists of four stages which are dissolution of materials, formation of C-A-S-H gels and ettringite, cementation of hydration products, and polycondensation of C-A-S-H gels. There are no strict boundaries among these four basic stages, and they proceed crossing each other. Moreover, the leaching toxicity tests were also performed to prove that the developed red mud-coal gangue based cementitious materials are environmentally acceptable. PMID:27131457

Self-cementitious properties of fly ash from circulating fluidized bed combustion boiler co-firing coal and high-sulphur petroleum coke (CPFA) were investigated. CPFA was self-cementitious which was affected by its fineness and chemical compositions, especially the contents of SO{sub 3} and free lime (f-CaO). Higher contents of SO{sub 3} and f-CaO were beneficial to self-cementitious strength; the self-cementitious strength increases with a decrease of its 45 {mu}m sieve residue. The expansive ratio of CPFA hardened paste was high because of generation of ettringite (AFt), which was influenced by its water to binder ratio (W/A), curing style and grinding of the ash. The paste cured in water had the highest expansive ratio, and grinding of CPFA was beneficial to its volume stability. The hydration products of CPFA detected by X-ray diffraction (XRD) and scanning electron microscopy (SEM) were portlandite, gypsum, AFt and hydrated calcium silicate (C-S-H)

In order to improve general monoscale information entropy methods like permutation and sample entropy in characterizing the irregularity of complex magnetospheric system, it is necessary to extend these entropy metrics to a multiscale paradigm. We propose novel multiscale and cross entropy method for the analysis of magnetospheric proxies such as auroral and polar cap indices during geomagnetic disturbance times. Such modified entropy metrics are certainly advantageous in classifying subsystems such as individual contributions of auroral electrojets and field aligned currents to high latitude magnetic perturbations during magnetic storm and polar substorm periods. We show that the multiscale entropy/cross entropy of geomagnetic indices vary with scale factor. These variations can be attributed to changes in multiscale dynamical complexity of non-equilibrium states present in the magnetospheric system. These types of features arise due to imbalance in injection and dissipation rates of energy with variations in magnetospheric response to solar wind. We also show that the multiscale entropy values of time series decrease during geomagnetic storm times which reveals an increase in temporal correlations as the system gradually shifts to a more orderly state. Such variations in entropy values can be interpreted as the signature of dynamical phase transitions which arise at the periods of geomagnetic storms and substorms that confirms several previously found results regarding emergence of cooperative dynamics, self-organization and non-Markovian nature of magnetosphere during disturbed periods.

Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models. PMID:22254341

We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology. PMID:24982249

Advanced model reduction methods were developed and integrated into the CMCS multiscale chemical science simulation software. The new technologies were used to simulate HCCI engines and burner flames with exceptional fidelity.

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. PMID:25810307

The use of bistable laminates is a potential approach to realize more broadband piezoelectric based energy harvesting systems. Based on the experimental time series of a bistable laminate plate we have examined its dynamic response. The system was subjected to harmonic excitations showing the existence of single well and snap-through vibrations of periodic and chaotic character. To identify the dynamics of the system response we examine the frequency spectrum, phase portraits and multi-scaled entropy. It is observed that the composite multiscale entropy analysis can be used to identify complexity within the dynamic response successfully.

Dislocation climb is a ubiquitous mechanism playing a major role in the plastic deformation of crystals at high temperature. We propose a multiscale approach to model quantitatively this mechanism at mesoscopic length and time scales. First, we analyze climb at a nanoscopic scale and derive an analytical expression of the climb rate of a jogged dislocation. Next, we deduce from this expression the activation energy of the process, bringing valuable insights to experimental studies. Finally, we show how to rigorously upscale the climb rate to a mesoscopic phase-field model of dislocation climb. This upscaling procedure opens the way to large scale simulations where climb processes are quantitatively reproduced even though the mesoscopic length scale of the simulation is orders of magnitude larger than the atomic one.

Dislocation climb is a ubiquitous mechanism playing a major role in the plastic deformation of crystals at high temperature. We propose a multiscale approach to model quantitatively this mechanism at mesoscopic length and time scales. First, we analyze climb at a nanoscopic scale and derive an analytical expression of the climb rate of a jogged dislocation. Next, we deduce from this expression the activation energy of the process, bringing valuable insights to experimental studies. Finally, we show how to rigorously upscale the climb rate to a mesoscopic phase-field model of dislocation climb. This upscaling procedure opens the way to large scale simulations where climb processes are quantitatively reproduced even though the mesoscopic length scale of the simulation is orders of magnitude larger than the atomic one. PMID:26765003

Genomic information is encoded on a wide range of distance scales, ranging from tens of base pairs to megabases. We developed a multiscale framework to analyze and visualize the information content of genomic signals. Different types of signals, such as GC content or DNA methylation, are characterized by distinct patterns of signal enrichment or depletion across scales spanning several orders of magnitude. These patterns are associated with a variety of genomic annotations, including genes, nuclear lamina associated domains, and repeat elements. By integrating the information across all scales, as compared to using any single scale, we demonstrate improved prediction of gene expression from Polymerase II chromatin immunoprecipitation sequencing (ChIP-seq) measurements and we observed that gene expression differences in colorectal cancer are not most strongly related to gene body methylation, but rather to methylation patterns that extend beyond the single-gene scale. PMID:24727652

Using the algorithm proposed by Costa M, et al., we studied the multiscale entropy (MSE) of electrocardiogram. The sample entropy (SampEn) of the healthy subjects was found to be higher than that of the subjects with coronary heart disease or myocardial infarction. The healthy subjects' complexity was found to be the highest. The SampEn of the subjects with coronary heart disease was noted to be only slightly higher than that of the subjects with myocardial infarction. These findings show that the complexity of the subjects with coronary heart disease or myocardial infarction is distinctly lower than the complexity of the healthy ones, and the subjects suffereing from coronary heart disease are liable to the onset of myocardial infarction. PMID:18027679

Polymer Nanocomposites are an important class of nanomaterials with potential applications including but not limited to structural and cushion materials, electromagnetic and heat shields, conducting plastics, sensors, and catalysts for various chemical and bio processes. Success in most such applications hinges on molecular-level control of structure and assembly, and a deep understanding of how the overall morphology of various components and the interfaces between them affect the composite properties at the macroscale. The length and time-scales associated with such assemblies are prohibitively large for a full atomistic modeling. Instead we adopt a multiscale methodology in which atomic-level interactions between different components of a composite are incorporated into a coarse-grained simulation of the mesoscale morphology, which is then represented on a numerical grid and the macroscopic properties computed using a finite-elements method.

Many studies consider media with microstructure, which has variations on some microscale, while the macroproperties are under investigation. Sometimes the medium has several microscales, all of them being much smaller than the macroscale. Sometimes the variations on the macroscale are also included, which are taken into account by some procedures, like WKB or geometric optics. What if the medium has variations on all scales from microscale to macroscale? This situation occurs in several practical problems. The talk is about such situations, in particular, passive tracer in a random velocity field, wave propagation in a random medium, Schrödinger equation with random potential. To treat such problems we have developed the statistical near-identity transformation. We find anomalous attenuation of the pulse propagating in a multiscale medium.

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.

Concrete cracking and deterioration can potentially be addressed by innovative self-healing cementitious materials, which can autogenously regain transport properties and mechanical characteristics after the damage self-healing process. For the development of such materials, it is crucial, but challenging, to precisely characterize the extent and quality of self-healing due to a variety of factors. This study adopted x-ray computed microtomography (μCT) to derive three-dimensional morphological data on microcracks before and after healing in engineered cementitious composite (ECC). Scanning electron microscope and energy dispersive x-ray spectroscopy were also used to morphologically and chemically analyze the healing products. This work showed that the evolution of the microcrack 3D structure due to self-healing in cementitious materials can be directly and quantitatively characterized by μCT. A detailed description of the μCT image analysis method applied to ECC self-healing was presented. The results revealed that the self-healing extent and rate strongly depended on initial surface crack width, with smaller crack width favoring fast and robust self-healing. We also found that the self-healing mechanism in cementitious materials is dependent on crack depth. The region of a crack close to the surface (from 0 to around 50-150 μm below the surface) can be sealed quickly with crystalline precipitates. However, at greater depths the healing process inside the crack takes a significantly longer time to occur, with healing products more likely resulting from continued hydration and pozzolanic reactions. Finally, the μCT method was compared with other self-healing characterization methods, with discussions on its importance in generating new scientific knowledge for the development of robust self-healing cementitious materials.

Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysis is complicated by inherent uncertainties as well as the limited information available to characterize the system. Any realistic modeling of these transport phenomena has to resolve two key issues: (i) the multi-length scale variations in permeability that these systems exhibit, and (ii) the inherently limited information available to quantify these property variations that necessitates posing these phenomena as stochastic processes. A stochastic variational multiscale formulation is developed to incorporate uncertain multiscale features. A stochastic analogue to a mixed multiscale finite element framework is used to formulate the physical stochastic multiscale process. Recent developments in linear and non-linear model reduction techniques are used to convert the limited information available about the permeability variation into a viable stochastic input model. An adaptive sparse grid collocation strategy is used to efficiently solve the resulting stochastic partial differential equations (SPDEs). The framework is applied to analyze flow through random heterogeneous media when only limited statistics about the permeability variation are given.

This project was concerned with the accurate computational error estimation for numerical solutions of multiphysics, multiscalesystems that couple different physical processes acting across a large range of scales relevant to the interests of the DOE. Multiscale, multiphysics models are characterized by intimate interactions between different physics across a wide range of scales. This poses significant computational challenges addressed by the proposal, including: (1) Accurate and efficient computation; (2) Complex stability; and (3) Linking different physics. The research in this project focused on Multiscale Operator Decomposition methods for solving multiphysics problems. The general approach is to decompose a multiphysics problem into components involving simpler physics over a relatively limited range of scales, and then to seek the solution of the entire system through some sort of iterative procedure involving solutions of the individual components. MOD is a very widely used technique for solving multiphysics, multiscale problems; it is heavily used throughout the DOE computational landscape. This project made a major advance in the analysis of the solution of multiscale, multiphysics problems.

This report is a collection of documents written as part of the Laboratory Directed Research and Development (LDRD) project A Mathematical Framework for Multiscale Science and Engineering: The Variational Multiscale Method and Interscale Transfer Operators. We present developments in two categories of multiscale mathematics and analysis. The first, continuum-to-continuum (CtC) multiscale, includes problems that allow application of the same continuum model at all scales with the primary barrier to simulation being computing resources. The second, atomistic-to-continuum (AtC) multiscale, represents applications where detailed physics at the atomistic or molecular level must be simulated to resolve the small scales, but the effect on and coupling to the continuum level is frequently unclear.

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of grains in orbit. An example of application is a spaceborne observatory for exoplanet imaging, where the primary aperture is a cloud instead of a monolithic aperture. A model is proposed of a multi-scale dynamics of the grains and cloud in orbit, as well as a control approach for cloud shape maintenance and alignment, and preliminary simulation studies are carried out for the representative imaging system.

The Multi-Scale Multi-Dimensional (MSMD) Lithium Ion Battery Model allows for computer prediction and engineering optimization of thermal, electrical, and electrochemical performance of lithium ion cells with realistic geometries. The model introduces separate simulation domains for different scale physics, achieving much higher computational efficiency compared to the single domain approach. It solves a one dimensional electrochemistry model in a micro sub-grid system, and captures the impacts of macro-scale battery design factors on cell performance and materialmore » usage by solving cell-level electron and heat transports in a macro grid system.« less

This paper discusses a multi-scale remote sensing modeling system that fuses flux assessments generated with TIR imagery collected by multiple satellite platforms to estimate daily surface fluxes from field to global scales. The Landsat series of polar orbiting systems has collected TIR imagery at 6...

Semi-flexible pavement surfacing is a composite pavement that utilizes the porous pavement structure of the flexible bituminous pavement, which is subsequently grouted with appropriate cementitious materials. This study aims to investigate the compressive strength, flexural strength, and workability performance of cementitious grout. The grout mixtures are designed to achieve high strength and maintain flow properties in order to allow the cement slurries to infiltrate easily through unfilled compacted skeletons. A paired-sample t-test was carried out to find out whether water/cement ratio, SP percentages, and use of silica fume influence the cementitious grout performance. The findings showed that the replacement of 5% silica fume with an adequate amount of superplasticizer and water/cement ratio was beneficial in improving the properties of the cementitious grout. PMID:24526911

Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation. But traditional multivariate multiscale entropy has a large quantity of computation and costs a large period of time and space for more channel system, so that it can not reflect the correlation between variables timely and accurately. In this paper, therefore, an improved multivariate multiscale entropy embeds on all variables at the same time, instead of embedding on a single variable as in the traditional methods, to solve the memory overflow while the number of channels rise, and it is more suitable for the actual multivariate signal analysis. The method was tested in simulation data and Bonn epilepsy dataset. The simulation results showed that the proposed method had a good performance to distinguish correlation data. Bonn epilepsy dataset experiment also showed that the method had a better classification accuracy among the five data set, especially with an accuracy of 100% for data collection of Z and S. PMID:26211236

This research paper investigated a novel absorbent of calcium aluminate-rich cementitious materials (Friedel's salt adsorbent, FA) for aqueous hexavalent chromium (VI) removal. The adsorption kinetics showed that the maximum adsorption capacities of FA were 3.36, 14.66, and 26.17 mg/g when the initial Cr(VI) concentration was 10, 50, and 100 mg/L, respectively. The adsorption fitted with the pseudo-second-order kinetic model, suggesting the important roles of intercalation in the adsorption process with increasing Cr(VI) concentrations. This Friedel's salt adsorbent is suggested as an adaptive and effective adsorbent for Cr(VI) removal in contaminated groundwater. PMID:25798557

Following needs of concrete market and the economic and ecological needs, several researchers, all over the world, studied the beneficial effect which the incorporation of the mineral additions in Portland cement industry can bring. It was shown that the incorporation of local mineral additions can decrease the consumption of crushing energy of cements, and reduce the CO2 emission. Siliceous additions, moreover their physical role of filling, play a chemical role pozzolanic. They contribute to improving concrete performances and thus their durability. The abundance of dunes sand and blast furnace slag in Algeria led us to study their effect like cementitious additions. The objective of this paper is to study the effect of the incorporation of dunes sand and slag, finely ground on rheological and mechanical properties of reactive powder concretes containing ternary binders.

This paper presents the fundamental properties of Ultra High Performance-Strain Hardening Cementitious Composites (UHP-SHCC), which were depeloped for repair applications. In particular, mechanical properties such as tensile response, shrinkage and bond strength were investigated experimentally. Protective performance of the material such as air permeability, water permeability and penetration of chloride ion was also confirmed comparing to that of ordinary concrete. This paper also introduces the usage of the material in repair of concrete st ructures. Laboratory tests concerining the deterioration induced by corrosion were conducted. The UHP-SHCC that coverd the RC beam resisted not only crack opening along the rebar due to corrosion but also crack opening due to loading tests.

A cementitious material was prepared by mixing 80wt% Si-Mn slag powder, 10wt% lime, and 10wt% anhydrite. The compressive strength of mortar samples reaches 51.48 MPa after 28 d curing. The analyses of X-ray diffraction (XRD) and scanning electron microscopy (SEM) show that much ettringite is formed in the sample cured for 3 d, and C-S-H gel increases rapidly during subsequent curing. Nuclear magnetic resonance (NMR) analysis of 29Si and 27Al and infrared spectroscopy (IR) analysis show that aluminum decomposition from tetrahedral network of the slag glass and its subsequent migration and re-combination play an important role in the process of hydration and strength development of the samples.

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, ormore » system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application

We are using the multi-scale technique to model bounded systems. Certain bounded systems are a naturally suited for the multi-scale method because of the boundary layer that forms at the wall, which is usually a short spatial and time scale structure, can significantly affect the bulk plasma behavior. One goal is to understand the interaction between the bulk plasma and the sheath. If the relevant short time scale physics is local to a few known spatial regions, then one can take advantage of this by advancing particles with variable {Delta}t depending on position, hence reducing computing time. The unmagnetized sheath problem is such a case. The model is a one dimensional bounded slab with kinetic ions and electrons. We start with a collisionless and unmagnetized system for simplicity. The right boundary is a conducting wall that absorbs all particles that come in contact with it. The left boundary is a symmetry point, where the particles are reflected. We allow a specified initial distribution: f(x,v,t = 0). In order to test the numerics of both multi-scale method and boundary conditions we are using the following test problem: a cutoff Maxwellian distribution for the electrons and fixed ions. The system has an analytic solution, so the run may be started from equilibrium. This gives us a benchmark and tests the fast time scale electron sheath dynamics. Results using variable {Delta}t will be given. In the future, we intend to use the more general model to study time dependent bounded plasma problems, such as a plasma expanding toward a conducting wall.

Investigated was bonding in steel fiber reinforced cementitious composites, like fiber-reinforced mortar. The study was basically analytical, consisting primarily of two analytical models that predict the bond shear stress distribution at the interface between the fibers and the matrix, as well as the normal tensile distributions in the fibers and the matrix. The two models were, however, based on separate assumptions. While the first model assumed a known bond shear stress versus slip relationship at the interface between the fibers and the surrounding matrix, the second model was based on a mechanism of force transfer between the fibers and the matrix, hence circumventing the rather complex task of determining the relationship between the bond stress and the slip for the given type of fiber and matrix. Some applications to this second model, such as the bond modulus, the debonding stress, the length of the debonded zone were also investigated. A theoretical study of the pull-out process of steel fibers in cementitious matrices is included. The problem consisted of relating an idealized bond shear stress versus slip relationship to a pull-out curve. The derivation as based on the assumption that this relationship is linearly elastic-perfectly frictional, and then extended to the case of a fiction decaying linearly with the slip. The problem was subdivided into two components: a primal problem, whereby the pull-out curve is predicted from an assumed bond shear stress-slip relationship, and the dual problem, in which an experimentally obtained pull-out curve was used to predict the interfacial constitutive model, namely the bond-slip curve. Model application was illustrated by three examples of pull-out tests. The pull-out curves obtained in the laboratory, which featured the pull-out force versus the end slip of the pull-out fiber, were used to predict bond shear stress-slip relationships.

The development of low-cost lightweight aggregate (LWA) mortars and concretes presents many advantages, especially in terms of lightness and thermal insulation performances of structures. Low-cost LWA mainly comes from the recovery of vegetal or plastic wastes. This article focuses on the characterization of the thermal conductivity of innovative lightweight cementitious composites made with fine particles of rigid polyurethane (PU) foam waste. Five mortars were prepared with various mass substitution rates of cement with PU-foam particles. Their thermal conductivity was measured with two transient methods: the heating-film method and the hot-disk method. The incorporation of PU-foam particles causes a reduction of up to 18 % of the mortar density, accompanied by a significant improvement of the thermal insulating performance. The effect of segregation on the thermal properties of LWA mortars due to the differences of density among the cementitious matrix, sand, and LWA has also been quantified. The application of the hot-disk method reveals a gradient of thermal conductivity along the thickness of the specimens, which could be explained by a non-uniform repartition of fine PU-foam particles and mineral aggregates within the mortars. The results show a spatial variation of the thermal conductivity of the LWA mortars, ranging from 9 % to 19 %. However, this variation remains close to or even lower than that observed on a normal weight aggregate mortar. Finally, a self-consistent approach is proposed to estimate the thermal conductivity of PU-foam cement-based composites.

Mechanotransduction has been divided into mechanotransmission, mechanosensing, and mechanoresponse, although how a cell performs all three functions using the same set of structural components is still highly debated. Here, we bridge the gap between emerging molecular and systems-level understandings of mechanotransduction through a multiscale model linking these three phases. Our model incorporates a discrete network of actin filaments and associated proteins that responds to stretching through geometric relaxation. We assess three potential activating mechanisms at mechanosensitive crosslinks as inputs to a mixture model of molecular release and benchmark each using experimental data of mechanically-induced Rho GTPase FilGAP release from actin-filamin crosslinks. Our results suggest that filamin-FilGAP mechanotransduction response is best explained by a bandpass mechanism favoring release when crosslinking angles fall outside of a specific range. Our model further investigates the difference between ordered versus disordered networks and finds that a more disordered actin network may allow a cell to more finely tune control of molecular release enabling a more robust response. PMID:25722249

Current cellular-based connectomics approaches aim to delineate the functional or structural organizations of mammalian brain circuits through neuronal activity mapping and/or axonal tracing. To discern possible connectivity between functionally identified neurons in widely distributed brain circuits, reliable and efficient network-based approaches of cross-registering or cross-correlating such functional-structural data are essential. Here, a novel cross-correlation approach that exploits multiple timing-specific, response-specific, and cell-specific neuronal characteristics as coincident fingerprint markers at the systems, network, and cellular levels is proposed. Application of this multiscale temporal-cellular coincident fingerprinting assay to the respiratory central pattern generator network in rats revealed a descending excitatory pathway with characteristic activity pattern and projecting from a distinct neuronal population in pons to its counterparts in medulla that control the post-inspiratory phase of the respiratory rhythm important for normal breathing, airway protection, and respiratory-vocalization coordination. This enabling neurotracing approach may prove valuable for functional connectivity mapping of other brain circuits. PMID:25056933

Magnetotellurics (MT) is a geophysical method based on the use of natural electromagnetic signals to define subsurface electrical resistivity structure through electromagnetic induction. MT waves are generated in the Earth's atmosphere and magnetosphere by a range of physical processes, such as magnetic storms, micropulsations, lightning activity. Since the underground MT wave propagation is of diffusive type, the longer is the wavelength (i.e. the lower the wave frequency) the deeper will be the propagation depth. Considering the frequency band commonly used in MT prospecting (10-4 Hz to 104 Hz), the investigation depth ranges from few hundred meters to hundreds of kilometers. This means that magnetotellurics is inherently a multiscale method and, thus, appropriate for applications at different scale ranging from aquifer system characterization to petroleum and geothermal research. In this perspective, the application of the Wavelet transform to the MT data analysis could represent an excellent tool to emphasize characteristics of the MT signal at different scales. In this note, the potentiality of such an approach is studied. In particular, we show that the use of a Discrete Wavelet (DW) decomposition of measured MT time-series data allows to retrieve robust information about the subsoil resistivity over a wide range of spatial (depth) scales, spanning up to 5 orders of magnitude. Furthermore, the application of DWs to MT data analysis has proven to be a flexible tool for advanced data processing (e.g. non-linear filtering, denoising and clustering).

Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

A mathematical and computational model combining the heart and circulatory system has been developed to understand the hemodynamics of circulation under normal conditions and ventricular septal defect (VSD). The immersed boundary method has been introduced to describe the interaction between the moving two-dimensional heart and intracardiac blood flow. The whole-heart model is governed by the Navier-Stokes system; this system is combined with a multi-compartment model of circulation using pressure-flow relations and the linearity of the discretized Navier-Stokes system. We investigate the velocity field, flowmeters, and pressure-volume loop in both normal and VSD cases. Simulation results show qualitatively good agreements with others found in the literature. This model, combining the heart and circulation, is useful for understanding the complex, hemodynamic mechanisms involved in normal circulation and cardiac diseases. PMID:26223734

Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain perfusion, as in the case of cerebral malaria. Modeling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangian method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behavior of whole healthy blood and compare with experimental results. The same procedure is applied to modeling malaria, and results for infected single RBCs and whole blood are presented.

We present an efficient multi-scale scheme to adaptively approximate the continuous (or densely sampled) contour of a planar shape at varying resolutions. The notion of shape is intimately related to the notion of contour, and the efficient representation of the contour of a shape is vital to a computational understanding of the shape. Any polygonal approximation of a planar smooth curve is equivalent to a piecewise constant approximation of the parameterized X and Y coordinate functions of a discrete point set obtained by densely sampling the curve. Using the Haar wavelet transform for the piecewise approximation yields a hierarchical scheme in which the size of the approximating point set is traded off against the morphological accuracy of the approximation. Our algorithm compresses the representation of the initial shape contour to a sparse sequence of points in the plane defining the vertices of the shape's polygonal approximation. Furthermore, it is possible to control the overall resolution of the approximation by a single, scale-independent parameter.

This work was conducted on Pinctada maxima nacre (mother of pearl) in order to understand its multiscale ordering and the role of the organic matrix in its structure. Intermittent-contact atomic force microscopy with phase detection imaging reveals a nanostructure within the tablet. A continuous organic framework divides each tablet into nanograins. Their shape is supposed to be flat with a mean extension of 45nm. TEM performed in the darkfield mode evidences that at least part of the intracrystalline matrix is crystallized and responds like a 'single crystal'. The tablet is a 'hybrid composite'. The organic matrix is continuous. The mineral phase is thus finely divided still behaving as a single crystal. It is proposed that each tablet results from the coherent aggregation of nanograins keeping strictly the same crystallographic orientation thanks to a hetero-epitaxy mechanism. Finally, high-resolution TEM performed on bridges from one tablet to the next, in the overlying row, did not permit to evidence a mineral lattice but crystallized organic bridges. The same organic bridges were evidenced by SEM in the interlaminar sequence. PMID:15907339

We present a set of multi-scale interlinked algorithms to model the dynamics of evolving foams. These algorithms couple the key effects of macroscopic bubble rearrangement, thin film drainage, and membrane rupture. For each of the mechanisms, we construct consistent and accurate algorithms, and couple them together to work across the wide range of space and time scales that occur in foam dynamics. These algorithms include second order finite difference projection methods for computing incompressible fluid flow on the macroscale, second order finite element methods to solve thin film drainage equations in the lamellae and Plateau borders, multiphase Voronoi Implicit Interface Methods to track interconnected membrane boundaries and capture topological changes, and Lagrangian particle methods for conservative liquid redistribution during rearrangement and rupture. We derive a full set of numerical approximations that are coupled via interface jump conditions and flux boundary conditions, and show convergence for the individual mechanisms. We demonstrate our approach by computing a variety of foam dynamics, including coupled evolution of three-dimensional bubble clusters attached to an anchored membrane and collapse of a foam cluster.

To quantitatively predict the mechanical response and mechanically induced remodeling of red blood cells, we developed a multiscale method to correlate distributions of internal stress with overall cell deformation. This method consists of three models at different length scales: in the complete cell level the membrane is modeled as two distinct layers of continuum shells using finite element method (Level III), in which the skeleton-bilayer interactions are depicted as a slide in the lateral (i.e., in-plane) direction (caused by the mobility of the skeleton-bilayer pinning points) and a normal contact force; the constitutive laws of the inner layer (the protein skeleton) are obtained from a molecular-based model (Level II); the mechanical properties of the spectrin (Sp, a key component of the skeleton), including its folding/unfolding reactions, are obtained with a stress-strain model (Level I). Model verification is achieved through comparisons with existing numerical and experimental studies in terms of the resting shape of the cell as well as cell deformations induced by micropipettes and optical tweezers. Detailed distributions of the interaction force between the lipid bilayer and the skeleton that may cause their dissociation and lead to phenomena such as vesiculation are predicted. Specifically, our model predicts correlation between the occurrence of Sp unfolding and increase in the mechanical load upon individual skeleton-bilayer pinning points. Finally a simulation of the necking process after skeleton-bilayer dissociation, a precursor of vesiculation, is conducted.

The Fast Plasma Investigation (FPI) on NASAs Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30 ms for electrons; 150 ms for ions) and spatially differentiated measurements of the full 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity, the reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions of magnetically reconnecting plasmas. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated using the plateau curve technique. In this, a fixed detection threshold is set. The detection system count rate is then measured as a function of MCP voltage to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection system discrimination threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully describe the behavior of the detection system and individually characterize each of its fundamental parameters. To improve this situation, we have developed a detailed phenomenological description of the detection system, its behavior and its signal, crosstalk and noise sources. Based on this, we have devised a new detection

The Colloquium and Workshop on Multiscale Coupled Modeling was held for the purpose of addressing modeling issues of importance to planning for the Cooperative Multiscale Experiment (CME). The colloquium presentations attempted to assess the current ability of numerical models to accurately simulate the development and evolution of mesoscale cloud and precipitation systems and their cycling of water substance, energy, and trace species. The primary purpose of the workshop was to make specific recommendations for the improvement of mesoscale models prior to the CME, their coupling with cloud, cumulus ensemble, hydrology, air chemistry models, and the observational requirements to initialize and verify these models.

The Magnetospheric Multiscale (MMS) mission consists of four formation-flying spacecraft placed in highly eccentric elliptical orbits about the Earth. The primary scientific mission objective is to study magnetic reconnection within the Earth s magnetosphere. The baseline navigation concept is the independent estimation of each spacecraft state using GPS pseudorange measurements (referenced to an onboard Ultra Stable Oscillator) and accelerometer measurements during maneuvers. State estimation for the MMS spacecraft is performed onboard each vehicle using the Goddard Enhanced Onboard Navigation System, which is embedded in the Navigator GPS receiver. This paper describes the latest efforts to characterize expected navigation flight performance using upgraded simulation models derived from recent analyses.

Magnetostatic Maxwell equations and the Landau-Lifshitz-Gilbert (LLG) equation are combined to a multiscale method, which allows to extend the problem size of traditional micromagnetic simulations. By means of magnetostatic Maxwell equations macroscopic regions can be handled in an averaged and stationary sense, whereas the LLG allows to accurately describe domain formation as well as magnetization dynamics in some microscopic subregions. The two regions are coupled by means of their strayfield and the combined system is solved by an optimized time integration scheme. PMID:24092951

Magnetostatic Maxwell equations and the Landau–Lifshitz–Gilbert (LLG) equation are combined to a multiscale method, which allows to extend the problem size of traditional micromagnetic simulations. By means of magnetostatic Maxwell equations macroscopic regions can be handled in an averaged and stationary sense, whereas the LLG allows to accurately describe domain formation as well as magnetization dynamics in some microscopic subregions. The two regions are coupled by means of their strayfield and the combined system is solved by an optimized time integration scheme. PMID:24092951

Magnetostatic Maxwell equations and the Landau-Lifshitz-Gilbert (LLG) equation are combined to a multiscale method, which allows to extend the problem size of traditional micromagnetic simulations. By means of magnetostatic Maxwell equations macroscopic regions can be handled in an averaged and stationary sense, whereas the LLG allows to accurately describe domain formation as well as magnetization dynamics in some microscopic subregions. The two regions are coupled by means of their strayfield and the combined system is solved by an optimized time integration scheme.

Ultra-high performance concrete (UHPC) is relatively a new generation of concretes optimized at the nano and micro-scales to provide superior mechanical and durability properties compared to conventional and high performance concretes. Improvements in UHPC are achieved through: limiting the water-to-cementitious materials ratio (i.e., w/cm ≤ 0.20), optimizing particle packing, eliminating coarse aggregate, using specialized materials, and implementing high temperature and high pressure curing regimes. In addition, and randomly dispersed and short fibers are typically added to enhance the material's tensile and flexural strength, ductility, and toughness. There is a specific interest in using UHPC for precast prestressed bridge girders because it has the potential to reduce maintenance costs associated with steel and conventional concrete girders, replace functionally obsolete or structurally deficient steel girders without increasing the weight or the depth of the girder, and increase bridge durability to between 75 and 100 years. UHPC girder construction differs from that of conventional reinforced concrete in that UHPC may not need transverse reinforcement due to the high tensile and shear strengths of the material. Before bridge designers specify such girders without using shear reinforcement, the long-term tensile performance of the material must be characterized. This multi-scale study provided new data and understanding of the long-term tensile performance of UHPC by assessing the effect of thermal treatment, fiber content, and stress level on the tensile creep in a large-scale study, and by characterizing the fiber-cementitious matrix interface at different curing regimes through nanoindentation and scanning electron microscopy (SEM) in a nano/micro-scale study. Tensile creep of UHPC was more sensitive to investigated parameters than tensile strength. Thermal treatment decreased tensile creep by about 60% after 1 year. Results suggested the possibility of

We have developed a multiscale modeling paradigm for the prediction of the viscoelastic properties, equation of state and yielding behavior of plastic bonded explosives (PBXs). In our multiscale modeling approach the components of the explosive (e.g., energetic material, metal and binder) are explicitly resolved and the material point method (MPM) is utilized to predict the response of the composite material to loading (isentropic, shock, etc.). This data are then utilized to develop equation-of-state and constitutive models for the PBX. The properties of the components are determined either from atomistic simulations or are taken from the literature. Force fields for the atomistic simulations in turn have been developed based upon high-level electronic structure calculations of model compounds and molecular complexes. Hence, our multiscale simulation approach systematically bridges length scales from atomistic to macroscopic. Applications of this approach to PBX-9501 and other PBXs will be considered.

This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.

In order to model the adhesive contact across different length scales, a multiscale approach is developed and used to study the adhesive contact behaviors between a rigid cylinder and an elastic face-centered cubic (FCC) substrate. The approach combines an atomistic treatment of the interfacial region with an elastic mechanics method description of the continuum region. The two regions are connected by a coupling region where nodes of the continuum region are refined to atoms of the atomistic region. Moreover, the elastic constants of FCC crystals are obtained directly from the Lennard-Jones potential to describe the elastic response characteristics of the continuum region, which ensures the consistency of material proprieties between atomistic and continuum regions. The multiscale approach is examined by comparing it with the pure MD simulation, and the results indicate that the multiscale modeling approach agrees well with the MD method in studying the adhesive contact behaviors.